Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach

Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach applied sciences Article Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach Ibrahim I. Falqi, Mohd Ahmed * and Javed Mallick Civil Engineering Department, College of Engineering, King Khalid University, Abha-6144, Saudi Arabia * Correspondence: mall@kku.edu.sa; Tel.: +966-172428439; Fax: +966-172418152 Received: 22 July 2019; Accepted: 10 August 2019; Published: 21 August 2019 Abstract: Concrete manufacturing, a high energy and natural resources demanding process, can play a vital role in sustainable development by o ering solutions to environmental and socio-economic issues. Concrete manufactured with siliceous materials can extend concrete life and reduce costs, and judicious management of siliceous utilization can make concrete manufacturing sustainable. A number of industrial and agro-based by-products, waste products, and new engineered materials are being use as siliceous material in concrete. The present research aims to implement the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for the orderly management of siliceous materials based on sustainable criteria, namely, technical, environmental, social, and economic aspects. The present research adopts twenty indicators of sustainability to evolve a comprehensive model for a sustainability ranking of concrete siliceous materials and to provide siliceous materials management. The present research also provides a methodology for the systematic ranking of sustainable criteria and indicators along with a siliceous materials sustainability order for enhanced sustainable development and management. It can be concluded that the proper material management of siliceous concrete materials, especially nano-engineered materials in construction industry, will help in the conservation of basic concrete materials and environmental protection without direct impact on social development. Keywords: concrete manufacturing; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS); multi criteria decision making; siliceous materials; management; sustainability 1. Introduction Concrete is basically manufactured by mixing aggregates with cementitious material. However, a number of construction materials, called admixtures, are added to improve or modify the concrete properties. The selection of such construction materials to provide an all-round performance of concrete is a complex process. Material selection is an important problem attracting theoretical and practical interest [1]. In the construction industry sector, the focus is increasingly on energy eciency and smart buildings with sustainability in infrastructure design and construction. Subsequently, appropriate materials must also be selected. Zavadskas et al. [2] has pointed out that construction material selection is a significant issue in the construction sector as the materials account for a considerable portion of a structure’s total cost. The unmanaged usage of material will not only a ect the economy of concrete construction but also badly a ect the environment and social development i.e., sustainable development. One of the solutions to reduce the use of basic concrete material and to make concrete economic, durable, and eco-friendly by adding siliceous materials. A number of siliceous materials, found as natural, industry/agro-based by-products, or other engineered materials, can be added as admixtures in concrete. A decade long comprehensive research review has been given by Stojcic et al. [3] for the application of decision-making approaches in sustainability engineering covering the topics from the selection of right stack holders, best process practices, and optimum materials to best options for management. Appl. Sci. 2019, 9, 3457; doi:10.3390/app9173457 www.mdpi.com/journal/applsci Appl. Sci. 2019, 9, 3457 2 of 15 Rashid et al. [4] used AHP and TOPSIS methods for the orderly management of building demolished materials such as ceramic waste aggregate and siliceous materials, to get the best performing sustainable concrete. An ecient assessment system using an MCDM-based distance approach (Entropy-TOPSIS) which considers the material energy eciency aspect for sustainability is due to Bhowmik et al. [5]. Stevic et al. [6] evaluate the potential location of roundabout construction for trac infrastructure using Rough BWM (Best Worst Method) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. The proposed model can capture the interrelationships among multi-input arguments and can provide decision makers more options. Mathiyazhagan et al. [7] frame an assessment model for evaluating and selecting sustainable building materials using a three-phase methodology i.e., triple bottom line (TBL)–best worst methodology (BWM)–Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Khoshnava et al. [8] implemented MCDM techniques to select energy-ecient, environmentally friendly, recyclable construction materials with regard to the technical, social, and environment aspects of sustainability. The model of selection based on environmental, social and economic impact was developed by Abeysundara et al. [9] for sustainable building materials and they found that environmental criteria should be given priority over social and economic criteria for sustainable building construction. Govindan et al. [10] has proposed and validated, via case study and respondent feedback, an integrated multi-criteria decision-making approach to sustainable choices of building materials. Bakhoum and Brown apply an embedded AHP–TOPSIS–entropy approach [11] to the ranking of sustainable structural material. Analytical Hierarch Process (AHP) and Choosing By Advantages (CBA) approaches have been used by Arroyo et al. to compare and select building material based on sustainable criteria [12]. The sustainability criteria related to environment, economic and social performance for residential buildings have been prioritized by Rahman et al. [13] using a Fuzzy Analytic Hierarchical Process. Ahmed et al. [14] applied a combined approach for the selection of siliceous materials satisfying sustainability issues. Erdogan et al. [15] used the Analytic Hierarchy Process (AHP) method and Expert Choice coding to select the best sustainable building management alternative. Akadiri [16] has examined the factors that hinder the selection of sustainable building materials by construction industry stockholders and identified that the perception of extra cost and the lack of information on the materials are the main obstacles for sustainable materials selection. Vinodh et al. [17] has carried out a case study on sustainable concept selection and pointed out that TOPSIS is the suitable MCDM technique for sustainable concept selection. The Fuzzy Extended Analytical Hierarchy Process (FEAHP) based sustainable material selection model is proposed by Akadiri et al. [18]. Dursun and Arslan [19] proposed an integrated decision framework for material selection procedure considering quality function deployment (QFD), 2-tuple fuzzy linguistic representation, and linguistic hierarchies. Zhang et al. [20] proposed a hybrid MCDM method combining decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA), and TOPSIS to the strategy selection of material for promoting sustainability development. Based on the above literature review, it is found that the applications of MCDM for the selection of sustainable construction materials, especially siliceous concrete materials, for construction industry are exceedingly scarce. The management of a vast number of siliceous concrete materials with a sustainable concept should be based on clearly defined sustainable indicators related to technical, environmental, and socio-economic issues. Therefore, the present research objective is to implement the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for orderly management of siliceous materials based on sustainable criteria, namely, technical, environmental, social and economic aspects and to promote sustainable development. Appl. Sci. 2019, 9, 3457 3 of 15 2. Materials and Methods 2.1. Selection of Sustainability Evaluation Indicators The sustainability indicators satisfying technical, environmental, and socio-economic criteria are framed to evaluate the sustainable management of siliceous concrete manufacturing material. Sustainability can be enhanced by considering indicators based on environmental, social, and economic aspects. In the present research, wide spectrums of indicators have been employed. In the ranking of siliceous concrete materials, the current model adopts eight, six, and three each of technical, environmental, social, and economic situations indices, respectively. The selected technical sustainability indices for concrete siliceous material includes siliceous material availability, relative proportion of concrete components, consistency of concrete mix, concrete compaction system, cohesiveness of concrete mix, concrete curing system, comply strength requirement of concrete mix, and comply durability requirements of concrete mix. The sustainability indicators for the selection of concrete siliceous material to attain environmental objectives include waste material utilization, concrete material conservation, reduction in carbon footprint, resistance to extreme exposure conditions, and energy conservation conformation to environmental standards. The sustainability indicators for concrete siliceous material to meet socio-economic objectives are considered as public welfare and safety, waste material cleaning, increased employment, life-long maintenance cost, concrete production cost, and siliceous material transportation cost. The Siliceous Concrete Materials Management for Sustainability approach is considered as a way for the concrete construction industry to move towards achieving sustainable development taking into account technical, environmental, socio and economic issues, as shown in Table 1. Sustainable materials management is also a way to portray the construction industry’s responsibility towards protecting the environment [21–24]. The practice of sustainable Siliceous Concrete Materials management refers to a process to develop construction industry that causes less harm to the environment—i.e., reducing the natural resources using basic construction materials and waste material management, reducing the environmental burdens of basic construction materials, reducing energy consumption in construction activities, reducing the burden on non-renewable construction materials; increasing durability against extreme exposure conditions; the use of standard recycled/sustainability sourced products, beneficial to the society, and profitable to the conduction industries. Material construction practitioners around the world are beginning to appreciate sustainability and recognize the benefits of implementing sustainable principles in concrete construction. The idea of sustainable materials, for instance, costs less than conventional materials and saves energy. Sustainable concrete material will make a positive contribution to improving quality of life, work eciency and a good working atmosphere. 2.2. Fuzzy TOPSIS Methodology Zadeh [25] implemented the concept of fuzzy sets theory to express the linguistic terms used in decision-making to alleviate the diculty of operational management. Hwang and Yoon [26] first suggested the TOPSIS method, a linear weighting technique. The weights can be assigned to the criteria using various methods such as mean weight (MW), entropy analysis, eigenvector method, standard deviation (SD), analytical network process (ANP), and analytical hierarchy process (AHP). The proposed MCDM based Fuzzy TOPSIS approach is implemented to the problem of ranking the sustainable concrete siliceous material. Based on an in-depth literature review, eleven of the most common siliceous concrete materials were identified. It includes Nano-Cement, Nano-Particles of Siliceous Material, Natural Pozzolana, Metakaolin, Silica Fume, Fly Ash, Rice Husk Ash, Lime Stone, Blast Furnace Slag, Recycled Aggregate, and Waste Glass. Figure 1 illustrates the fuzzy-TOPSIS based framework for the ranking of sustainable siliceous concrete materials management. Appl. Sci. 2019, 9, 3457 4 of 15 Appl. Sci. 2019, 9, x FOR PEER REVIEW 4 of 17 Figure 1. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS) based Figure 1. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS) framework for ranking of sustainable siliceous concrete material management. based framework for ranking of sustainable siliceous concrete material management. Table 1. Sustainable criteria along with sustainability indicators (sub-criteria) for selection of siliceous The experts with commendable experience in concrete technology were asked to judge and rank concrete materials and their principal issues. the selected sustainable criteria and sustainable indicators. A questionnaire (Sample Questionnaire- Title Sustainability Criteria Principal Issues 1, Appendix A) based on linguistics terms and triangular fuzzy number (TFN) was offered for siliceous material availability establishing the importance of the criteria and role of siliceous concrete material towards relative proportion of sustainability. Questionnaire-1 used five linguistic terms [27], namely, Very Low, Low, Medium, concrete components High, and Very High, along with corresponding triangular fuzzy numbers (TFN) of (0,0.1,0.3), consistency of concrete mix properly managed construction materials utilization; protection concrete compaction system (0.1,0.3,0.5), (0.3,0.5,0.7), (0.5,0.7,0.9), and (0.7,0.9,1), respectively, reflecting the importance weights technical of sensitive ecosystems through good construction practices and Cohesiveness of concrete mix sustainability supervision; technically proven high preformation construction of each performance criteria in providing sustainability in siliceous concrete material. Later, on Concrete curing system materials; low water consumption during production. Questionnaire-2 (Append  Comply ix B) w strength as administered which used five linguistic terms [28], namely, Very requirement of concrete mix Poor, Poor, Fair, Good and Very Good, along with corresponding triangular fuzzy numbers (TFN) of Comply durability (0,1,3), (1,3,5), (3,5,7), (5,7,9), and (7,9,10) to ascertain the role of each concrete siliceous material to requirements of concrete mix provide the much needed sustainability on the selected set of twenty criteria. The overall performance Waste material utilization Reduction of natural resources using basic construction Concrete of each concrete siliceous material was documented. In order to find the preferential sustainable materials and waste material management; reduction of the material conservation concrete siliceous material, the selected criteria were further utilized to rate the performance of each Environmental  Reduction in carbon environmental burdens of basic construction materials; preferent sustainability ial concrete foot siliprint ceous material using Ze reduction leny’s [ of2ener 9] opin gy consumption ion. Accor in dconstr ing to uction Hwang activities; and Yoon Resistance to extreme reduction of the burdens on non-renewable construction [26], in comparison with others, the selected option should have the optimal distance (most close to exposure conditions materials; increased durability against extreme exposure positive and farthest from adverse) i.e., alternatives should not only be the shortest distance from the Energy conservation conditions; use of standard recycled/sustainability Conformation to sourced products. positive ideal reference point (PIRP) but also the longest distance from the negative ideal reference environmental standards point (NIRP). The algorithm used in this method is described in the following section. Health, safety and conducive working environment; minimizing Public welfare and safety local nuisance and disruption; contributing to the local economy Social Table 1. Sustainable criteria along with sustainability indicators (sub-criteria) for selection of siliceous through local employment and procurement; building long-term Waste material cleaning sustainability relationships with local suppliers; minimizing strain on land concrete materi  als and Increased their pr employment incipal issues. resources and improving of overall quality of life. Sustainability Improved productivity; employee economic satisfaction; lower Title Principal Issues Life-long maintenance cost cost projects with increased cost predictability; delivering Criteria Economic  Concrete production cost services that provide best value to clients; supplier satisfaction; • siliceous material sustainability client satisfaction with minimum defects; low cost maintenance; Siliceous material availability low cost product through minimum transportation cost; transportation cost optimized life-cycle economic performance. • relative properly managed construction materials utilization; proportion of concrete protection of sensitive ecosystems through good technical The experts with components commendable experience construction practices in concrete technology and supervision were asked to ; te judge chnically and rank sustainability • consistency of proven high preformation construction materials; low the selected sustainable criteria and sustainable indicators. A questionnaire (Sample Questionnaire-1, Appendix A) based concrete mix on linguistics terms and water consumption durin triangular fuzzy number g product (TFN) ion. was o ered for • concrete compaction system Appl. Sci. 2019, 9, 3457 5 of 15 establishing the importance of the criteria and role of siliceous concrete material towards sustainability. Questionnaire-1 used five linguistic terms [27], namely, Very Low, Low, Medium, High, and Very High, along with corresponding triangular fuzzy numbers (TFN) of (0,0.1,0.3), (0.1,0.3,0.5), (0.3,0.5,0.7), (0.5,0.7,0.9), and (0.7,0.9,1), respectively, reflecting the importance weights of each performance criteria in providing sustainability in siliceous concrete material. Later, on Questionnaire-2 (Appendix B) was administered which used five linguistic terms [28], namely, Very Poor, Poor, Fair, Good and Very Good, along with corresponding triangular fuzzy numbers (TFN) of (0,1,3), (1,3,5), (3,5,7), (5,7,9), and (7,9,10) to ascertain the role of each concrete siliceous material to provide the much needed sustainability on the selected set of twenty criteria. The overall performance of each concrete siliceous material was documented. In order to find the preferential sustainable concrete siliceous material, the selected criteria were further utilized to rate the performance of each preferential concrete siliceous material using Zeleny’s [29] opinion. According to Hwang and Yoon [26], in comparison with others, the selected option should have the optimal distance (most close to positive and farthest from adverse) i.e., alternatives should not only be the shortest distance from the positive ideal reference point (PIRP) but also the longest distance from the negative ideal reference point (NIRP). The algorithm used in this method is described in the following section. 2.2.1. Construction of the Fuzzy Decision Matrix for Sustainability Problem Given m alternatives for sustainable concrete siliceous material, n selection criteria, and k expert group of professionals, a typical fuzzy decision matrix for sustainability problem can be expressed as below: 1 2 n SC SC :::::: SC 2 3 a a a 6 11 12 1n 7 6 7 6  7 6 7 6 7 a a a 6 22 2n 7 A (1) 2 6 7 e 6 7 D= , i = 1, 2,:::::: , m; j = 1, 2, :::::: , n 6 7 . . . 6 . 7 6 . . . . 7 6 . 7 . . . 6 7 6 7 4 5 a a  a n1 n2 nn where A , A , ::: , A are the alternatives materials to be chosen, SC , SC , ::: , SC denote the n n 1 2 1 2 sustainability evaluation criteria for concrete siliceous material, D represents the rating of alternative ij materials A with respect to sustainability criterion SC evaluated by k experts. Since the perception i j toward ranking the sustainable concrete siliceous material is subject to an individual’s experience, intuition, or knowledge, this study, therefore, uses the technique of average value to integrate the fuzzy performance score e x for k experts concerning the same evaluation criteria, that is ij 1 2 k e x = (e x + e x + ::: + e x (2) ij ij ij ij where e x is the rating of alternative Ai with respect to criterion SCj evaluated by the k expert and ij k k k k e x = a , b , c . (3) ij ij ij ij 2.2.2. Normalization of the Fuzzy Decision Matrix for Sustainability Problem The various criteria required to select the sustainable concrete siliceous material are measured in di erent units and therefore need to be normalized. The current study adopts linear scales to transform the normalization function for preserving the property of the ranges of normalized TFN to be included in [0, 1]. If R denotes the normalized fuzzy decision matrix, then h i R= e r , I = 1, 2,:::::: , m; j = 1, 2, :::::: , n (4) ij mxn Appl. Sci. 2019, 9, 3457 6 of 15 a b c ij ij ij where r = , , ij + + + sc sc sc j j j SC = maxSC (5) ij 2.2.3. Construction of Weighted Normalized Fuzzy Decision Matrix for Sustainability Problem Considering the di erent weight of each sustainability criterion, the weighted normalized decision matrix can be computed by multiplying the importance weights of the evaluation criteria and the values in the normalized fuzzy decision matrix. The weighted normalized decision matrix e v is defined as h i e= e , i = 1, 2,:::::: , m; j = 1, 2, :::::: , n (6) ij mxn e e = r w (7) ij ij j where w represents the importance weight of criterion C obtained through j j 1 2 k e e e e w = w + w + ::: + w (8) j j j where k is the number of expert members in a group and w e represents the fuzzy weight of j criteria assessed by kth expert” 2.2.4. Determination of the FPIRP and FNIRP The fuzzy negative ideal reference point (FNIRP, A ) and fuzzy positive ideal reference point (FPIRP, A ) in the interval [0, 1] can be represented as: + + + + e e e A =  ,  ,::: (9) 1 2 A = e , e ,:::e (10) 1 2 e e where  = (1, 1, 1) and  = (0, 0, 0), j = 1, 2, ::: ..,n j j 2.2.5. Calculation for the Distances of Each Concrete Siliceous Material to FPIRP and FNIRP The distance of each concrete siliceous material alternate from the fuzzy positive ideal reference point (FPIRP) and the fuzzy negative ideal reference point (FNIRP) can be derived respectively as + + d = d(e , e ), i = 1, 2,:::::: , n; j = 1, 2, :::::: , n (11) ij i j j=1 e e d = d( ,  ), i = 1, 2,:::::: , m; j = 1, 2, :::::: , n (12) ij i j j=1 e e where, d  ,  , denotes the distance measurement between two fuzzy numbers, d represents the ij j distance of alternative L from FPIRP, and d is the distance of alternative L from FNIRP. i i 2.2.6. Process to Obtain the Closeness Coecient and Rank the Order of Alternatives Once the closeness coecient (CC) is determined, the ranking order of all alternatives can be obtained, allowing the decision-makers to select the most feasible alternative. The closeness coecient of each alternative is calculated as cc = i = 1, 2, 3, :::::: m (13) d + D i i Appl. Sci. 2019, 9, 3457 7 of 15 An option with index cc approaching 1 shows that the option is near to the fuzzy positive ideal reference point and far from the fuzzy negative ideal reference point. A large proximity index value indicates a good performance of the option Ai. 2.2.7. Assessment of Sustainable Concrete Siliceous Material The ranking of concrete siliceous materials with sustainability objectives is a multi-criteria decision-making process. After the initial problem formulation, expert advice and opinion may be sought to determine the sustainable assessment criteria and indicators. Experts may employ their vast experience and expertise while ranking concrete siliceous material according to their merits in sustainability. The use of linguistic terms and corresponding TFN will help to make their decision in fuzzy based assessment. The fuzzy TOPSIS methodology was employed. The five experts were asked to judge the role of the criteria in providing sustainability. They were also asked to judge the role of each concrete siliceous material in providing sustainability. The detailed methodology adopted in ranking the concrete siliceous material, as per the closeness to sustainability goals, is documented in the following section. 3. Results 3.1. Calculation of the Synthetic Importance Weights of Evaluation Criteria The expert group expressed their opinion in linguistics terms for their preference of sustainability evaluation indicators [27], namely Very Low, Low, Medium, High, and Very High, corresponding to its TFN. An integrated fuzzy importance weight matrix for evaluation criteria was generated using the method of average value described in Equation (7). To understand the importance order of these selection criteria, the center of area (COA) method [30] was utilized to de-fuzzify TFN into corresponding best non-fuzzy performance (BNP) values. The twenty most important sustainable indicators for assessing concrete siliceous materials for sustainability with corresponding BNP values are presented in Table 2 as SC (0.66), SC (0.72), SC (0.70), SC (0.7267), SC (0.76), SC (0.72), SC 1 2 3 4 5 6 7 (0.6867), SC (0.42), SC (0.7667), SC (0.8667), SC (0.80), SC (0.7667), SC (0.7333), SC (0.7667), 8 9 10 11 12 13 14 SC (0.4133), SC (0.3933), SC (0.38), SC (0.4267), SC (0.40), and SC (0.46). The maximum BNP 15 16 17 18 19 20 value was obtained for the sustainable indicator of “concrete material conservation (SC )”, while the minimum BNP value was obtained for the sustainable indicator of “increased employment (SC )”. 3.1.1. Construction of the Fuzzy Decision Matrix The ranking of concrete siliceous materials is an important issue for sustainable concrete objectives. In order to accomplish sustainability goals, a systematic performance analysis of various sustainability criteria and their indicators was carried out. The experts gave their feedback in linguistic terms. The experts used the linguistic terms Very Poor, Poor, Fair, Good and Very Good along with TFN, as depicted in Appendix A, to express their opinions for each concrete siliceous material based on their individual capability against each sustainability evaluation indicator. The fuzzy performance ratings of each concrete siliceous material regarding evaluation indicators were averaged to synthesize the various individual judgments. With Equation (1), the synthetic fuzzy decision matrix can be computed, as shown in Table 3. Fuzzy weights were obtained after normalizing the BNP values. Appl. Sci. 2019, 9, 3457 8 of 15 Table 2. Fuzzy importance weight, best non-fuzzy performance (BNP), and rank of each indicator. Indicator Description of the Indicator Fuzzy Importance Weight BNP Values Rank SC Concrete curing system (0.460,0.660,0.860) 0.6600 13 SC Concrete compaction system (0.540,0.740,0.880) 0.7200 9 SC Cohesiveness of concrete mix (0.500,0.700,0.900) 0.7000 11 SC Consistency of concrete mix (0.540,0.740,0.900) 0.7267 8 SC Comply strength requirement of concrete mix (0.580,0.780,0.920) 0.7600 6 SC Comply durability requirements of concrete mix (0.5400.740,0.880) 0.7200 9 SC Relative proportion of concrete components (0.500,0.700,0.860) 0.6867 12 SC Siliceous material availability (0.220,0.420,0.620) 0.4200 16 SC Energy conservation (0.580,0.780,0.940) 0.7667 3 SC Concrete material conservation (0.700,0.900,1.000) 0.8667 1 SC Waste material utilization (0.620,0.820,0.960) 0.8000 2 SC Conformation to environmental standards (0.580,0.780,0.940) 0.7667 5 SC Reduction in carbon foot print (0.540,0.740,0.920) 0.7333 7 SC Resistance to extreme exposure conditions (0.580,0.780,0.940) 0.7667 3 SC Waste material cleaning (0.220,0.420,0.600) 0.4133 17 SC Public welfare and safety (0.240,0.380,0.560) 0.3933 19 SC Increased employment (0.220,0.420,0.500) 0.3800 20 SC Concrete production cost (0.240,0.420,0.6200 0.4267 15 SC Siliceous material transportation cost (0.240,0.400,0.560) 0.4000 18 SC Lifelong maintenance cost (0.260,0.460,0.660) 0.4600 14 3.1.2. Calculation of Normalized Fuzzy Decision Matrix and Weighted Normalized Matrix To ensure that the normalized triangular fuzzy numbers are included in the interval [0, 1], the linear scale transforms function is used. The synthetic fuzzy decision matrices were normalized using the Equations (2)–(4), and the results are shown in Table 4. Normalization process was carried out by dividing each row by the maximum of that row. The normalized values are shown in the table. The normalized fuzzy numbers were later applied on importance weights and since the importance weights of criteria are di erent, Equations (6) and (7) was employed for the fuzzy weighted normalized decision matrix, results are shown in Table 5. 3.1.3. Determination of the Fuzzy Positive and Fuzzy Negative Ideal Reference Points As the positive TFN are in the range of [0, 1], so the fuzzy positive ideal reference point and fuzzy negative ideal reference point can be defined as A = [(1, 1, 1), (1, 1, 1), (1, 1, 1), (1, 1, 1), (1, 1, 1)] (14) A = [(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0)] (15) 3.1.4. Calculation for the Distance of Each Concrete Siliceous Material to FPIRP and FNIRP and Determining the Closeness Coecient (CC) for Ranking of Concrete Siliceous Material The distance of each concrete siliceous material to the FPIRP and FNIRP can be calculated using Equations (10) and (11). Once the distances of concrete siliceous material from FPIRP and FNIRP are determined, the closeness coecient for the concrete siliceous material alternatives can be obtained with Equation (12). Closeness coecients are calculated based on the obtained FPIRP and FNIRP. The distances of concrete siliceous material from FPIRP and FNIRP, the closeness coecient and ranking of various concrete siliceous materials are shown in Table 6. Figure 2 depicts the graphical representation of concrete siliceous materials ranking as per the obtained Closeness Coecients. Appl. Sci. 2019, 9, 3457 9 of 15 Table 3. The fuzzy decision matrix of sustainable siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (3.400,5.400,7.400 (0.600,2.200,4.200) (0.800,2.600,4.600) 2.600,4.600,6.600) (0.800,2.600,4.600) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.200,4.200,6.200) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (1.000,3.000,5.000 (2.600,4.600,6.600) (0.600,2.200,4.200) 2.200,4.200,6.200) (1.000,3.000,5.000) (0.400,1.800,3.800) (2.600,4.600,6.600) (2.800,4.600,6.600) (0.400,1.800,3.800) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (1.400,3.400,5.400) (2.200,4.200,6.200) (2.600,4.600,6.600) 3.000,5.000,7.000) (0.800,2.600,4.600) (2.600,4.600,6.600) (3.000,5.000,7.000) (2.600,4.600,6.600) (2.400,4.200,6.200) (3.000,5.000,7.000) (3.000,5.000,7.000) SC (1.000,3.000,5.000) (4.600,6.600,8.600) (2.200,4.200,6.200) 1.000,3.000,5.000) (1.400,3.400,5.400) (2.600,4.600,6.600) (6.200,8.200,9.600) (3.000,5.000,7.000) (1.800,3.800,5.800) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (1.000,3.000,5.000) (0.800,2.400,4.000) (4.600,6.600,8.600) 3.800,5.800,7.800) (0.600,1.800,3.800) (0.200,1.400,3.400) (3.800,5.800,7.800) (4.600,6.600,8.600) (0.200,1.400,3.400) (0.200,1.400,3.400) (0.200,1.400,3.400) SC 0.200,1.200,3.400) (0.600,2.200,4.200) (0.800,2.400,4.600) 2.400,4.000,5.600) (0.000,0.800,2.400) (0.200,1.200,3.800) (2.400,4.000,5.600) (1.600,3.200,5.400) (0.200,1.200,2.800) (0.200,1.200,2.800) (0.200,1.200,2.800) SC (0.200,1.400,3.400) (2.600,4.600,6.600) (0.600,2.200,4.200) 3.000,5.000,7.000) (0.000,1.000,3.000) (2.600,4.600,6.600) (3.000,5.000,7.000) (0.600,2.200,4.200) (1.000,2.600,4.600) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.200,1.400,3.400) (2.200,4.200,6.200) (2.600,4.600,6.600) 1.800,3.800,5.800) (0.000,1.000,3.000) (2.600,4.600,6.600) (6.200,8.200,9.600) (3.400,5.400,7.400) (1.600,3.400,5.400) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.000,1.000,3.000) (4.000,5.800,7.800) (2.200,4.200,6.200) 1.800,3.800,5.800) (0.000,1.000,3.000) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.600,4.600,6.600) (0.000,1.000,3.000) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (0.200,1.400,3.400) (4.000,5.800,7.800) (4.000,5.800,7.800) 2.600,4.600,6.600) (1.000,3.000,5.000) (0.400,1.800,3.800) (2.600,4.600,6.600) (4.000,5.800,7.800) (0.200,1.400,3.400) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (0.000,1.000,3.000) (0.800,2.600,4.600) (0.800,2.600,4.600) 1.400,3.400,5.400) (1.000,3.000,5.000) (2.600,4.600,6.600) (3.000,5.000,7.000) (2.000,3.800,5.800) (1.000,2.600,4.600) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.400,1.800,3.800) (2.600,4.600,6.600) (0.800,2.600,4.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (2.600,4.600,6.600) (6.200,8.200,9.600) (0.400,1.800,3.800) (1.200,3.000,5.000) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (1.000,3.000,5.000) (2.600,4.600,6.600) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.200,3.000,5.000) (4.600,6.600,8.600) (6.600,8.600,9.800) (2.600,4.600,6.600) (4.200,6.200,8.200) (4.600,6.600,8.600) (4.600,6.600,8.600) SC (1.000,3.000,5.000) (4.200,6.200,8.200) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (1.400,3.400,5.400) (3.400,5.400,7.400) (4.200,6.200,8.200) (1.000,3.000,5.000) (1.400,3.400,5.400) (1.400,3.400,5.400) SC (1.800,3.800,5.800) (2.600,4.600,6.600) (4.200,6.200,8.200) 1.800,3.800,5.800) (1.000,3.000,5.000) (0.800,2.600,4.600) (3.800,5.800,7.800) (2.600,4.600,6.600) (1.800,3.800,5.800) (0.800,2.600,4.600) (0.800,2.600,4.600) SC (2.200,4.200,6.000) (4.600,6.600,8.600) (2.600,4.600,6.600) 2.200,4.200,6.000) (1.000,3.000,5.000) (0.400,1.800,3.800) (5.400,7.400,9.200) (1.800,3.800,5.800) (1.800,3.400,5.200) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (1.800,3.800,5.800) (2.600,4.600,6.600) (1.400,3.400,5.400) 2.600,4.600,6.600) (1.000,3.000,5.000) (0.400,1.800,3.800) (3.400,5.400,7.400) (2.600,4.600,6.600) (1.200,2.600,4.600) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (3.400,5.400,7.400) (4.600,6.600,8.600) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.600,4.600,6.600) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (3.800,5.800,7.800 (4.600,6.600,8.600) (1.400,0.400,5.400) 1.800,3.800,5.800) (1.400,3.400,5.400) (0.400,1.800,3.800) (3.800,5.800,7.800) (2.200,4.200,6.200) (1.400,3.000,5.000) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (5.400,7.400,9.200) (0.600,2.200,4.200) (1.800,3.800,5.800) 5.400,7.400,9.200) (1.800,3.800,5.800) (0.200,1.400,3.400) (5.400,7.400,9.200) (2.200,4.200,6.200) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) Table 4. The fuzzy normalized decision matrix of sustainable siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (0.436,0.692,0.949) (0.103,0.333,0.590) (0.103,0.333,0.590) (0.333,0.590,0.846) (0.103,0.333,0.590) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.282,0.538,0.795) (0.154,0.333,0.590) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.152,0.455,0.758) (0.091,0.333,0.636) (0.091,0.333,0.636) (0.333,0.636,0.939) (0.152,0.455,0.758) (0.061,0.273,0.576) (0.394,0.697,1.000) (0.424,0.697,1.000) (0.061,0.273,0.576) (0.061,0.273,0.576) (0.061,0.273,0.576) SC (0.200,0.486,0.771) (0.371,0.657,0.943) (0.371,0.657,0.943) (0.429,0.714,1.000) (0.114,0.371,0.657) (0.371,0.657,0.943) (0.429,0.714,1.000) (0.371,0.657,0.943) (0.343,0.600,0.886) (0.429,0.714,1.000) (0.429,0.714,1.000) SC (0.104,0.313,0.521) (0.229,0.438,0.646) (0.229,0.438,0.646) (0.104,0.313,0.521) (0.146,0.354,0.563) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.313,0.521,0.729) (0.188,0.396,0.604) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.116,0.349,0.581) (0.535,0.767,1.000) (0.535,0.767,1.000) (0.442,0.674,0.907) (0.070,0.209,0.442) (0.023,0.163,0.395) (0.442,0.674,0.907) (0.535,0.767,1.000) (0.023,0.163,0.395) (0.023,0.163,0.395) (0.023,0.163,0.395) SC (0.036,0.214,0.607) (0.143,0.429,0.714) (0.143,0.429,0.821) (0.429,0.714,1.000) (0.000,0.143,0.429) (0.036,0.214,0.679) (0.429,0.714,1.000) (0.286,0.571,0.964 (0.036,0.214,0.500) (0.036,0.214,0.500) (0.036,0.214,0.500) SC (0.029,0.200,0.486) (0.086,0.314,0.600) (0.086,0.314,0.600) (0.429,0.714,1.000) (0.000,0.143,0.429) (0.371,0.657,0.940) (0.429,0.714,1.000) (0.086,0.314,0.600) (0.143,0.371,0.657) (0.371,0.657,0.943) (0.371,0.657,0.943) SC (0.021,0.146,0.354) (0.271,0.479,0.688) (0.271,0.479,0.688) (0.188,0.396,0.604) (0.000,0.104,0.313) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.354,0.563,0.771) (0.167,0.354,0.563) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.000,0.128,0.385) (0.282,0.538,0.795) (0.282,0.538,0.795) (0.231,0.487,0.744) (0.000,0.128,0.385) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.333,0.590,0.846) (0.000,0.128,0.385) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.026,0.179,0.436) (0.513,0.744,1.000) (0.513,0.744,1.000) (0.333,0.590,0.846) (0.128,0.385,0.641) (0.051,0.231,0.487) (0.333,0.590,0.846) (0.513,0.744,1.000) (0.026,0.179,0.436) (0.051,0.231,0.487) (0.051,0.231,0.487) SC (0.000,0.128,0.385) (0.513,0.744,1.000) (0.103,0.333,0.590) (0.179,0.436,0.692) (0.128,0.385,0.641) (0.333,0.590,0.846) (0.385,0.641,0.897) 90.256,0.487,0.744 (0.128,0.333,0.590) (0.333,0.590,0.846) (0.333,0.590,0.846) SC (0.042,0.188,0.396) (0.083,0.271,0.470) (0.083,0.271,0.479) (0.188,0.396,0.604) (0.104,0.313,0.521) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.042,0.188,0.396) (0.125,0.313,0.521) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.102,0.306,0.510) (0.265,0.469,0.673) (0.265,0.469,0.673) (0.184,0.388,0.592) (0.122,0.306,0.510) (0.469,0.673,0.878) (0.673,0.878,1.000) (0.265,0.469,0.673) (0.429,0.633,0.837) (0.469,0.673,0.878) (0.469,0.673,0.878) SC (0.135,0.405,0.676) (0.351,0.622,0.892) (0.351,0.622,0.892) (0.243,0.514,0.784) (0.135,0.405,0.676) (0.189,0.459,0.730) (0.459,0.730,1.000) (0.351,0.622,0.892) (0.135,0.405,0.676 (0.189,0.459,0.730) (0.189,0.459,0.730) SC (0.220,0.463,0.707) (0.512,0.756,1.000) (0.512,0.756,1.000) (0.220,0.463,0.707) (0.122,0.366,0.610) (0.098,0.317,0.561) (0.463,0.707,0.950) (0.512,0.756,1.000) (0.220,0.463,0.707) (0.098,0.317,0.561) (0.098,0.317,0.561) SC (0.239,0.457,0.652) (0.283,0.500,0.717) (0.283,0.500,0.717) (0.239,0.457,0.652) (0.109,0.326,0.540) (0.043,0.196,0.413) (0.587,0.804,1.000) (0.283,0.500,0.717) (0.196,0.370,0.565) (0.043,0.196,0.413) (0.043,0.196,0.413) SC (0.209,0.442,0.674) (0.535,0.767,1.000) (0.163,0.395,0.628) (0.302,0.535,0.767) (0.116,0.349,0.581) (0.047,0.209,0.442) (0.395,0.628,0.860) (0.209,0.442,0.674) (0.140,0.302,0.535) (0.047,0.209,0.442) (0.047,0.209,0.442) SC (0.436,0.692,0.949) (0.333,0.590,0.846) (0.333,0.590,0.846) (0.231,0.487,0.744) (0.128,0.385,0.641) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.333,0.590,0.846) (0.154,0.333,0.590) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.442,0.674,0.907) (0.535,0.767,1.000) (0.163,0.395,0.628) (0.209,0.442,0.674) (0.163,0.395,0.628) (0.047,0.209,0.442) (0.442,0.674,0.907) (0.302,0.535,0.767) (0.163,0.349,0.581) (0.047,0.209,0.442) (0.047,0.209,0.442) SC (0.587,0.804,1.000) (0.500,0.717,0.935) (0.196,0.413,0.630) (0.587,0.804,1.000) (0.196,0.413,0.630) (0.022,0.152,0.370) (0.587,0.804,1.000) (0.239,0.457,0.674) (0.130,0.283,0.500) (0.022,0.152,0.370) (0.022,0.152,0.370) 20 Appl. Sci. 2019, 9, 3457 10 of 15 Table 5. The fuzzy weighted normalized decision matrix of Sustainable Siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (0.201,0.457,0.816) (0.047,0.220,0.507) (0.047,0.220,0.507) (0.153,0.389,0.728) (0.047,0.220,0.507) (0.012,0.118,0.375) (0.224,0.491,0.860) (0.130,0.355,0.684) (0.071,0.220,0.507) (0.012,0.118,0.375) (0.012,0.118,0.375) SC (0.082,0.336,0.667) (0.049,0.247,0.560) (0.049,0.247,0.560) (0.180,0.471,0.827) (0.082,0.3360.652) (0.033,0.202,0.507) (0.213,0.516,0.880) (0.229,0.516,0.880) (0.033,0.202,0.507) (0.033,0.202,0.507) (0.033,0.202,0.507) SC (0.100,0.340,0.694) (0.186,0.460,0.849) (0.186,0.460,0.849) (0.214,0.500,0.900) (0.057,0.260,0.565) (0.186,0.460,0.849) (0.214,0.500,0.900) (0.186,0.460,0.849) (0.171,0.420,0.797) (0.214,0.500,0.900) (0.214,0.500,0.900) SC (0.056,0.231,0.469) (0.124,0.324,0.581) (0.124,0.324,0.581) (0.056,0.231,0.469) (0.079,0.262,0.484) (0.146,0.355,0.619) (0.349,0.632,0.900) (0.169,0.385,0.656) (0.101,0.293,0.544) (0.146,0.355,0.619) (0.146,0.355,0.619) SC (0.067,0.272,0.535) (0.310,0.599,0.920) (0.310,0.599,0.920) (0.256,0.526,0.834) (0.040,0.163,0.380) (0.013,0.127,0.364) (0.256,0.526,0.834) (0.310,0.599,0.920) (0.013,0.127,0.364) (0.013,0.127,0.364) (0.013,0.127,0.364) SC (0.019,0.159,0.534) (0.077,0.317,0.629) (0.077,0.317,0.723) (0.231,0.529,0.880) (0.000,0.106,0.369) (0.019,0.159,0.597) (0.231,0.529,0.880) (0.154,0.423,0.849) (0.019,0.159,0.440) (0.019,0.159,0.440 (0.019,0.159,0.440) SC (0.014,0.140,0.418) (0.043,0.220,0.516) (0.043,0.220,0.516) (0.214,0.500,0.860) (0.000,0.100,0.369) (0.186,0.460,0.811) (0.214,0.500,0.860) (0.043,0.220,0.516) (0.071,0.260,0.565) (0.186,0.460,0.811) (0.186,0.460,0.811) SC (0.005,0.061,0.220) (0.060,0.201,0.426) (0.060,0.201,0.426) (0.041,0.166,0.375) (0.000,0.044,0.269) (0.060,0.201,0.426) (0.142,0.359,0.620) (0.078,0.236,0.478) (0.037,0.149,0.349) (0.060,0.201,0.426) (0.060,0.201,0.426) SC (0.000,0.100,0.362) (0.164,0.420,0.747) (0.164,0.420,0.747) (0.134,0.380,0.699) (0.000,0.100,0.331) (0.015,0.140,0.410) (0.283,0.580,0.940) (0.193,0.460,0.795) (0.000,0.100,0.362) (0.015,0.140,0.410) (0.015,0.140,0.410) SC (0.018,0.162,0.436) (0.359,0.669,1.000) (0.359,0.669,1.000) (0.233,0.531,0.846) (0.090,0.346,0.551) (0.036,0.208,0.487) (0.233,0.531,0.846) (0.359,0.669,1.000) (0.018,0.162,0.436) (0.036,0.208,0.487) (0.036,0.208,0.487) SC (0.000,0.105,0.369) (0.318,0.610,0.960) (0.064,0.273,0.566) (0.111,0.357,0.665) (0.079,0.315,0.551) (0.207,0.484,0.812) (0.238,0.526,0.862) (0.159,0.399,0.714) (0.079,0.273,0.566) (0.207,0.484,0.812) (0.207,0.484,0.812) SC (0.024,0.146,0.372) (0.048,0.211,0.450) (0.048,0.211,0.450) (0.109,0.309,0.568) (0.060,0.244,0.448) (0.157,0.374,0.646) (0.375,0.666,0.940) (0.024,0.146,0.372) (0.073,0.244,0.490) (0.157,0.374,0.646) (0.157,0.374,0.646) SC (0.055,0.227,0.469) (0.143,0.347,0.620) (0.143,0.347,0.620) (0.099,0.287,0.544) (0.066,0.227,0.439) (0.253,0.498,0.807) (0.364,0.649,0.920) (0.143,0.347,0.620) (0.231,0.468,0.770) (0.253,0.498,0.807) (0.253,0.498,0.807) SC (0.078,0.316,0.635) (0.204,0.485,0.838) (0.204,0.485,0.838) (0.141,0.401,0.737) (0.078,0.316,0.581) (0.110,0.358,0.686) (0.266,0.569,0.940) (0.204,0.485,0.838) (0.078,0.316,0.635) (0.110,0.358,0.686) (0.110,0.358,0.686) SC (0.048,0.195,0.424) (0.113,0.318,0.600) (0.113,0.318,0.600) (0.048,0.195,0.424) (0.027,0.154,0.524) (0.021,0.133,0.337) (0.102,0.297,0.571) (0.113,0.318,0.600) (0.048,0.195,0.424) (0.021,0.133,0.337) (0.021,0.133,0.337) SC (0.057,0.173,0.365) (0.068,0.190,0.402) (0.068,0.190,0.402) (0.057,0.173,0.365) (0.026,0.124,0.467) (0.010,0.074,0.231) (0.141,0.306,0.560) (0.068,0.190,0.402) (0.047,0.140,0.317) (0.010,0.074,0.231) (0.010,0.074,0.231) SC (0.046,0.186,0.337) (0.118,0.322,0.500) (0.036,0.166,0.314) (0.067,0.225,0.384) (0.026,0.147,0.500) (0.010,0.088,0.221) (0.087,0.264,0.430) (0.046,0.186,0.337) (0.031,0.127,0.267) (0.010,0.088,0.221) (0.010,0.088,0.221) SC (0.105,0.291,0.588) (0.080,0.248,0.525) (0.080,0.248,0.525) (0.055,0.205,0.461) (0.031,0.162,0.551) (0.006,0.075,0.270 (0.117,0.312,0.620) (0.080,0.248,0.525) (0.037,0.140,0.366) (0.006,0.075,0.270) (0.006,0.075,0.270) SC (0.106,0.270,0.508) (0.128,0.307,0.560) (0.039,0.158,0.352) (0.050,0.177,0.378) (0.039,0.158,0.540) ((.011,0.084,0.247 (0.106,0.270,0.508) (0.073,0.214,0.430) (0.039,0.140,0.326) (0.011,0.084,0.247) (0.000,0.084,0.247) SC (0.153,0.370,0.660) (0.130,0.330,0.617) (0.051,0.190,0.416) (0.153,0.370,0.660) (0.051,0.190,0.542) 0(.006,0.070,0.244 (0.153,0.370,0.660) (0.062,0.210,0.445) (0.034,0.130,0.330) (0.006,0.070,0.244) (0.006,0.070,0.244) 20 Appl. Sci. 2019, 9, 3457 11 of 15 Table 6. The fuzzy positive ideal reference point (FPIRP) and fuzzy negative ideal reference point (FNIRP) distances, closeness coecients and rank of each sustainable siliceous materials. + - d d Supplementary Material Alternatives cc Ranking i i Limestone A 15.2620 6.3464 0.2937 9 Blast Furnace Slag A 13.2325 8.6205 0.3945 3 Metakaolin A 13.8836 7.9110 0.3630 5 Fly Ash A 13.3874 8.4508 0.3870 4 Rise Husk Ash A 15.6305 6.0714 0.2798 10 Silica Fume A 15.1549 6.4536 0.2987 6 Appl. Sci. 2019, 9, x FOR PEER REVIEW 2 of 17 Nano-Cement A 11.3468 10.790 0.4874 1 Nano-Particles Supp. Mat. A 13.2058 8.6757 0.3965 2 Recycled Aggregate A9 15.4692 6.0042 0.2796 11 Recycled Aggregate A 15.4692 6.0042 0.2796 11 Waste Glass A 15.1564 6.4067 0.2971 7 Waste Glass A10 15.1564 6.4067 0.2971 7 Natural Pozolona A 15.1606 6.4065 0.2971 8 Natural Pozolona A11 15.1606 6.4065 0.2971 8 0.6 0.5 0.4 0.3 0.2 0.1 Figure 2. Ranking of each alternative material based on closeness coecient. Figure 2. Ranking of each alternative material based on closeness coefficient. 4. Discussion 4. Discussion The Fuzzy-TOPSIS based approach has been implemented to manage the use of siliceous concrete The Fuzzy-TOPSIS based approach has been implemented to manage the use of siliceous materials for sustainable development. Mahmoudkelaye et al. [21] applied the Analytic Network concrete materials for sustainable development. Mahmoudkelaye et al. [21] applied the Analytic Process (ANP) as a multi-criteria decision-making method for sustainable material selection for Network Process (ANP) as a multi-criteria decision-making method for sustainable material selection building, considering the holistic impact of materials on the environment through sustainable criteria for building, considering the holistic impact of materials on the environment through sustainable which are marked as economic, technical, socio-cultural, and environmental factors. The importance criteria which are marked as economic, technical, socio-cultural, and environmental factors. The of the criteria and sub-criteria in choosing sustainable materials was determined through this model. importance of the criteria and sub-criteria in choosing sustainable materials was determined through Whereas, the present study implements the Fuzzy Technique for Order of Preference by Similarity to this model. Whereas, the present study implements the Fuzzy Technique for Order of Preference by Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for orderly Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) management of siliceous materials based on sustainable criteria, namely, technical, environmental, technique, for orderly management of siliceous materials based on sustainable criteria, namely, social and economic aspects and to promote sustainable development. Various sustainable criteria technical, environmental, social and economic aspects and to promote sustainable development. viz. technical, environmental and socio-economical, are considered. It has been observed that, Various sustainable criteria viz. technical, environmental and socio-economical, are considered. It has in accomplishing the sustainable goals for siliceous concrete materials, the environmental criteria play been observed that, in accomplishing the sustainable goals for siliceous concrete materials, the a central role, whereas the social criteria play the minor role. It has also been observed that the most environmental criteria play a central role, whereas the social criteria play the minor role. It has also e ective sustainable indicator for the ranking of siliceous concrete materials is “concrete material been observed that the most effective sustainable indicator for the ranking of siliceous concrete materials is “concrete material conservation”. It indicates that concrete material conservation is a major issue in sustainable material management and the use of siliceous concrete material should be mandatory in the construction industry for sustainable development. The least effective sustainable indicator observed is the “enhanced employment”, and siliceous concrete materials application has no major impact on social development. Among the eleven selected siliceous concrete materials, nano-engineered materials, namely, nano-cement and nano-particles of siliceous material should be given top priority in material management for the manufacturing of sustainable concrete product. The siliceous materials come next for sustainable concrete construction. The recycled material to be used as siliceous concrete materials occupies the lowest rank among the sustainable concrete materials. The ranking of the material in descending order of preference to produce sustainable concrete is: Nano-cement > Nano-particles of siliceous material > Blast Furnace Slag > Fly Ash > CC Limestone 0.2937 Blast Furnace Slag 0.3944 0.3629 Metakaolin 0.3869 Fly Ash 0.2797 Rise Husk Ash Silica Fume 0.2986 Nano-Cement 0.4874 Nano-Particles supp. 0.3964 Mat. 0.2796 Recycled Aggregate Waste glass 0.2971 0.2971 Natural Pozolona Appl. Sci. 2019, 9, 3457 12 of 15 conservation”. It indicates that concrete material conservation is a major issue in sustainable material management and the use of siliceous concrete material should be mandatory in the construction industry for sustainable development. The least e ective sustainable indicator observed is the “enhanced employment”, and siliceous concrete materials application has no major impact on social development. Among the eleven selected siliceous concrete materials, nano-engineered materials, namely, nano-cement and nano-particles of siliceous material should be given top priority in material management for the manufacturing of sustainable concrete product. The siliceous materials come next for sustainable concrete construction. The recycled material to be used as siliceous concrete materials occupies the lowest rank among the sustainable concrete materials. The ranking of the material in descending order of preference to produce sustainable concrete is: Nano-cement > Nano-particles of siliceous material > Blast Furnace Slag > Fly Ash > Metakaolin > Silica Fume > Waste Glass > Natural Pozolona > Lime Stone > Rice Husk Ash > Recycled Aggregate, where ‘>’ represents preference over other concrete material. The corresponding closeness coecients of the eleven siliceous concrete materials are: 0.4874 > 0.3965 > 0.3945 > 0.3870 > 0.3630 > 0.2987 > 0.2971 > 0.2971 > 0.2937 > 0.2798 > 0.2796 where ‘>’ represents the preference over other concrete material. 5. Conclusions The construction industry must look for a sustainability framework to overcome global resources scarcity and environmental impact by adopting sustainable material management in the concrete manufacturing processes. The proper material management is required to select the siliceous material for the production of concrete product from the ever increasing sources of siliceous materials such as industrial waste products, agro-waste products, building recycled material, natural pozolonic material, and siliceous engineered material. The much needed sustainability may be accrued by considering factors related to technique and the environment as well as socio-economic factors while selecting siliceous concrete materials. Concrete manufacturing, through material management, must adapt to environmental friendly material and processes, which should not only be cost-e ective but also provide economic value and safety for society. In the present study, more comprehensive criteria are selected in order to provide sustainability. Moreover, the study adopts twenty sustainability indicators for siliceous concrete materials, thus covering the material management sustainability aspects to a larger extent. It is found from the adopted MCDM approach that among the selected sustainable indicators, the most e ective sustainable indicator for managing siliceous materials is concrete material conservation. The least governing sustainable indicator is enhanced employment. It can be concluded from the study that the large scale use of siliceous concrete materials in construction industry will help in the conservation of basic concrete materials and environmental protection, though it will not have direct impact on social development. The proposed material management model for siliceous materials suggests that the material could be best utilized for sustainable development by the classifying the various siliceous materials into two groups i.e., Group I with CC > 0.35 and Group II with CC < 0.35. The selected siliceous concrete materials, namely, Nano-cement and Nano-particles of siliceous material, Blast Furnace Slag, Fly Ash, and Metakaoline exhibit larger CC value and are hence classified as Group I materials, which possess higher potential of providing sustainability. The siliceous concrete materials of Silica Fume, Waste Glass, Natural Pozolona, Lime Stone, and Rice Husk Ash exhibit lower values of CC, and hence may be regarded as having lower capability towards achieving sustainability in comparison to the Group II. The nano-engineered material, although costly, will prove to be the best material for sustainable concrete construction and development. The current research provides just a preliminary framework for the selection of basic materials for concrete construction in alignment with sustainability. In selecting sustainable siliceous concrete materials, this research has opened opportunities for further research in sustainable materials. The results of this study can be further expanded and modified to achieve the ultimate objective of encouraging and improving sustainable construction methods. The present research will be of great Appl. Sci. 2019, 9, 3457 13 of 15 importance for the concrete industry dealing with concrete manufacturing and to tackle the challenges like increased manufacturing costs, higher concrete performance requirements, and being risk-free to the environment and society. Author Contributions: Conceptualization and formal analysis, I.I.F. and M.A.; methodology, software, and validation, J.M., I.I.F., M.A., J.M.; writing—original draft preparation, I.I.F. and M.A.; writing—review and editing, J.M.; supervision and project administration, I.I.F., M.A.; funding acquisition, M.A. Funding: This research was funded by Deanship of Scientific Research King Khalid University, grant number 172 (1440) and the APC was funded by authors. Acknowledgments: The authors thankfully acknowledge the Deanship of Scientific Research for proving administrative and financial support. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Questionaire for Fuzzy TOPSIS With respect to the overall goal of “Selection of the Sustainable Siliceous Materials” Sample questions included in questionnaire Q1. How importance is the Sustainable Indicator Support for Concrete Curing System in the rating of 1–9 scale? (C ) Q2. What importance do you assign to Sustainable Indicator Support to Concrete Compaction System in the rating of 1–9 scale? (C )? Q3. What importance do you assign to Sustainable Indicator Support to Cohesiveness of Concrete Mix in the rating of 1–9 scale? (C )? Q4. What importance do you assign to Sustainable Indicator Support to Consistency of Concrete Mix in the rating of 1–9 scale? (C )? Q5. What importance do you assign to Sustainable Indicator Comply Strength Requirement of Concrete Mix in the rating of 1–9 scale? (C )? With Respect to Sustainable Importance (or Preference) of Each Criterion Siliceous Materials. Sustainable (0,0.1,0.3) (0.1,0.3,0.5) (0.3,0.5,0.7) (0.5,0.7,0.9) (0.7,0.9,1) Questions Indicator Very Low Low Medium High Very High Q1 C Q2 C Q3 C Q4 C Appendix B Scoring of Alternatives with Respect to Sustainable Indicator for Overall Goal of “Sustainable Siliceous Materials” Q2-1. What scores do you assign to A with reference to Sustainable Indicator Support to Concrete Curing System (C ) in the rating of 1–9 scale? Q2-2. What scores do you assign to A with reference to Sustainable Indicator Support to Concrete Compaction System (C ) in the rating of 1–9 scale? Q2-3. What scores do you assign to A with reference to Sustainable Indicator Support to Cohesiveness of Concrete Mix (C ) in the rating of 1–9 scale? Q2-4. What scores do you assign to A with reference to Sustainable Indicator Support to Consistency of Concrete Mix (C ) in the rating of 1–9 scale? Q2-5. What scores do you assign to A with reference to Sustainable Indicator Comply Strength Requirement of Concrete Mix (C ) in the rating of 1–9 scale? 5 Appl. Sci. 2019, 9, 3457 14 of 15 With Respect to the Sustainable Performance of Each Sustainable Siliceous Materials Siliceous Materials Alternative with Respect to Each Sustainable Indicator Sustainable Sustainable (0,1,3) Very (1,3,5) (5,7,9) (7,9,10) Questions (3,5,7) Fair Indicator Siliceous Materials Poor Poor Good Very Good Q2-1 C A 1 1 Q2-2 C A 2 1 Q2-3 C A 3 1 Q2-4 C A 4 1 Q2-5 C A 5 1 References 1. Babanli, M.B.; Prima, F.; Vermaut, P.; Demchenko, L.D.; Titenko, A.N.; Huseynov, S.S.; Hajiyev, R.J.; Huseynov, V.M. Material Selection Methods: A Review. In Theory and Application of Fuzzy Systems and Soft Computing; Aliev, R.A., Ed.; ICAFS-2018, AISC 896; Springer Nature AG: Geneve, Switzerland, 2019; pp. 929–936. [CrossRef] 2. Zavadskas, E.K.; Kaklauskas, A.; Saparauskas, J. Sustainable urban development and web-based Multiple Criteria Analysis. Found. Civ. Environ. Eng. 2005, 6, 217–226. 3. Stojci ˇ c, ´ M.; Zavadskas, E.K.; Pamucar ˇ , D.; Stevic, ´ Ž.; Mardani, A. Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018. Symmetry 2019, 11, 350. [CrossRef] 4. Rashid, K.; Razzaq, A.; Ahmad, M.; Rashid, T.; Tariq, S. Experimental and analytical selection of sustainable recycled concrete with ceramic waste aggregate. Constr. Build. Mater. 2017, 154, 829–840. [CrossRef] 5. Bhowmik, C.; Gangwar, S.; Bhowmik, S.; Ray, A. Optimum Selection of Energy-Ecient Material: A MCDM-Based Distance Approach. In Soft Computing Applications. Studies in Computational Intelligence; Ray, K., Pant, M., Bandyopadhyay, A., Eds.; Springer: Singapore, 2018; p. 761. 6. Stevic, Z.; Pamucar, D.; Subotic, M.; Antucheviciene, J.; Zavadskas, E.K. The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator. Sustainability 2018, 10, 2817. [CrossRef] 7. Mathiyazhagan, K.; Gnanavelbabu, A.; Lokesh, P.B. A sustainable assessment model for material selection in construction industries perspective using hybrid MCDM approaches. J. Adv. Manag. Res. 2019, 16, 234–259. [CrossRef] 8. Khoshnava, S.M.; Rostami, R.; Valipour, A.; Ismail, M.; Rahmat, A.R. Rank of green building material criteria based on the three pillars of sustainability using the hybrid multi criteria decision making method. J. Clean. Prod. 2018, 173, 82–99. [CrossRef] 9. Abeysundara, U.G.Y.; Babel, S.; Gheewala, S. A matrix in life cycle perspective for selecting sustainable materials for buildings in Sri Lanka. Build. Environ. 2009, 44–45, 997–1004. [CrossRef] 10. Govindan, K.; Shankar, K.M.; Kannan, D. Sustainable material selection for construction industry—A hybrid multi criteria decision making approach. Renew. Sustain. Energy Rev. 2016, 55, 1274–1288. [CrossRef] 11. Bakhoum, E.; Brown, D. A hybrid approach using for sustainable ranking of structural materials. Int. J. Sustain. Eng. 2013, 6, 212–224. [CrossRef] 12. Arroyo, P.; Tommelein, I.D.; Ballard, G. Selecting Globally Sustainable Materials: A Case Study Using Choosing by Advantages. J. Constr. Eng. Manag. 2015, 142, 05015015. [CrossRef] 13. Rahman, H.A.; Wang, C.; Wood, L.C.; Ebrahimi, M. Integrating and ranking sustainability criteria for housing. Proc. Inst. Civ. Eng. Eng. Sustain. 2017, 169, 3–30. 14. Ahmed, M.; Qureshi, M.N.; Mallick, J.; Kahla, N.B. Selection of Sustainable Supplementary Concrete Materials Using OSM-AHP-TOPSIS Approach. Adv. Mater. Sci. Eng. 2019, 5, 2850480. [CrossRef] 15. Erdogan, S.A.; Saparauskas, J.; Turskis, Z. A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management. Sustainability 2019, 11, 2239. [CrossRef] 16. Akadiri, P.O. Understanding barriers a ecting the selection of sustainable materials in building projects. J. Build. Eng. 2015, 4, 86–93. [CrossRef] 17. Vinodh, S.; Mulanjur, G.; Thiagarajan, A. Sustainable Concept Selection Using Modified Fuzzy TOPSIS: A Case Study. Int. J. Sustain. Eng. 2013, 6, 109–116. [CrossRef] Appl. Sci. 2019, 9, 3457 15 of 15 18. Akadiri, P.O.; Olomolaiye, P.O.; Chinyio, E.A. Multi-Criteria Evaluation Model for the Selection of Sustainable Materials for Building Projects. Autom. Constr. 2013, 30, 113–125. [CrossRef] 19. Dursun, M.; Arslan, O. An Integrated Decision Framework for Material Selection Procedure: A Case Study in a Detergent Manufacturer. Symmetry 2018, 10, 657. [CrossRef] 20. Zhang, H.; Peng, Y.; Tian, G.; Wang, D.; Xie, P. Green material selection for sustainability: A hybrid MCDM approach. PLoS ONE 2017, 12, e0177578. [CrossRef] 21. Mahmoudkelaye, S.; Azari, K.T.; Pourvaziri, M.; Asadian, E. Sustainable material selection for building enclosure through ANP method. Case Stud. Constr. Mater. 2018, 9, 00200. [CrossRef] 22. Ding, G.K.C. Sustainable construction—The role of environmental assessment tools. J. Environ. Manag. 2008, 86, 451–464. [CrossRef] 23. Abidin, N.Z. Investigating the awareness and application of sustainable construction concept by Malaysian developers. Habitat Int. 2010, 34, 421–426. [CrossRef] 24. Shen, L.; Tam, V.; Tam, L.; Ji, Y. Project feasibility study: The key to successful implementation of sustainable and socially responsible construction management practice. J. Clean. Prod. 2010, 18, 254–259. [CrossRef] 25. Zadeh, L.A. Fuzzy sets. Inf. Control 1965, 8, 338–353. [CrossRef] 26. Hwang, C.L.; Yoon, K. Multiple Attributes Decision Making Methods and Applications, a State-of-the-Art Survey; Taylor & Francis Group: New York, NY, USA, 1981. 27. Wang, M.J.; Chang, T.C. Tool steel materials selection under fuzzy environment. Fuzzy Sets Syst. 1995, 72, 263–270. [CrossRef] 28. Chen, C.T. Extensions of the TOPSIS for group decisi.on-making under fuzzy environment. Fuzzy Sets Syst. 2000, 114, 1–9. [CrossRef] 29. Zeleny, M. A Concept of Compromise Solutions and the Method of the Displaced Ideal. Comput. Oper. Res. 1974, 1, 479–496. [CrossRef] 30. Zhao, R.; Govind, R. Algebraic characteristics of extended fuzzy numbers. Inf. Sci. 1991, 54, 103–130. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Sciences Multidisciplinary Digital Publishing Institute

Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach

Applied Sciences , Volume 9 (17) – Aug 21, 2019

Loading next page...
 
/lp/multidisciplinary-digital-publishing-institute/siliceous-concrete-materials-management-for-sustainability-using-fuzzy-51JJ4LlZHj
Publisher
Multidisciplinary Digital Publishing Institute
Copyright
© 1996-2019 MDPI (Basel, Switzerland) unless otherwise stated
ISSN
2076-3417
DOI
10.3390/app9173457
Publisher site
See Article on Publisher Site

Abstract

applied sciences Article Siliceous Concrete Materials Management for Sustainability Using Fuzzy-TOPSIS Approach Ibrahim I. Falqi, Mohd Ahmed * and Javed Mallick Civil Engineering Department, College of Engineering, King Khalid University, Abha-6144, Saudi Arabia * Correspondence: mall@kku.edu.sa; Tel.: +966-172428439; Fax: +966-172418152 Received: 22 July 2019; Accepted: 10 August 2019; Published: 21 August 2019 Abstract: Concrete manufacturing, a high energy and natural resources demanding process, can play a vital role in sustainable development by o ering solutions to environmental and socio-economic issues. Concrete manufactured with siliceous materials can extend concrete life and reduce costs, and judicious management of siliceous utilization can make concrete manufacturing sustainable. A number of industrial and agro-based by-products, waste products, and new engineered materials are being use as siliceous material in concrete. The present research aims to implement the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for the orderly management of siliceous materials based on sustainable criteria, namely, technical, environmental, social, and economic aspects. The present research adopts twenty indicators of sustainability to evolve a comprehensive model for a sustainability ranking of concrete siliceous materials and to provide siliceous materials management. The present research also provides a methodology for the systematic ranking of sustainable criteria and indicators along with a siliceous materials sustainability order for enhanced sustainable development and management. It can be concluded that the proper material management of siliceous concrete materials, especially nano-engineered materials in construction industry, will help in the conservation of basic concrete materials and environmental protection without direct impact on social development. Keywords: concrete manufacturing; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS); multi criteria decision making; siliceous materials; management; sustainability 1. Introduction Concrete is basically manufactured by mixing aggregates with cementitious material. However, a number of construction materials, called admixtures, are added to improve or modify the concrete properties. The selection of such construction materials to provide an all-round performance of concrete is a complex process. Material selection is an important problem attracting theoretical and practical interest [1]. In the construction industry sector, the focus is increasingly on energy eciency and smart buildings with sustainability in infrastructure design and construction. Subsequently, appropriate materials must also be selected. Zavadskas et al. [2] has pointed out that construction material selection is a significant issue in the construction sector as the materials account for a considerable portion of a structure’s total cost. The unmanaged usage of material will not only a ect the economy of concrete construction but also badly a ect the environment and social development i.e., sustainable development. One of the solutions to reduce the use of basic concrete material and to make concrete economic, durable, and eco-friendly by adding siliceous materials. A number of siliceous materials, found as natural, industry/agro-based by-products, or other engineered materials, can be added as admixtures in concrete. A decade long comprehensive research review has been given by Stojcic et al. [3] for the application of decision-making approaches in sustainability engineering covering the topics from the selection of right stack holders, best process practices, and optimum materials to best options for management. Appl. Sci. 2019, 9, 3457; doi:10.3390/app9173457 www.mdpi.com/journal/applsci Appl. Sci. 2019, 9, 3457 2 of 15 Rashid et al. [4] used AHP and TOPSIS methods for the orderly management of building demolished materials such as ceramic waste aggregate and siliceous materials, to get the best performing sustainable concrete. An ecient assessment system using an MCDM-based distance approach (Entropy-TOPSIS) which considers the material energy eciency aspect for sustainability is due to Bhowmik et al. [5]. Stevic et al. [6] evaluate the potential location of roundabout construction for trac infrastructure using Rough BWM (Best Worst Method) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. The proposed model can capture the interrelationships among multi-input arguments and can provide decision makers more options. Mathiyazhagan et al. [7] frame an assessment model for evaluating and selecting sustainable building materials using a three-phase methodology i.e., triple bottom line (TBL)–best worst methodology (BWM)–Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Khoshnava et al. [8] implemented MCDM techniques to select energy-ecient, environmentally friendly, recyclable construction materials with regard to the technical, social, and environment aspects of sustainability. The model of selection based on environmental, social and economic impact was developed by Abeysundara et al. [9] for sustainable building materials and they found that environmental criteria should be given priority over social and economic criteria for sustainable building construction. Govindan et al. [10] has proposed and validated, via case study and respondent feedback, an integrated multi-criteria decision-making approach to sustainable choices of building materials. Bakhoum and Brown apply an embedded AHP–TOPSIS–entropy approach [11] to the ranking of sustainable structural material. Analytical Hierarch Process (AHP) and Choosing By Advantages (CBA) approaches have been used by Arroyo et al. to compare and select building material based on sustainable criteria [12]. The sustainability criteria related to environment, economic and social performance for residential buildings have been prioritized by Rahman et al. [13] using a Fuzzy Analytic Hierarchical Process. Ahmed et al. [14] applied a combined approach for the selection of siliceous materials satisfying sustainability issues. Erdogan et al. [15] used the Analytic Hierarchy Process (AHP) method and Expert Choice coding to select the best sustainable building management alternative. Akadiri [16] has examined the factors that hinder the selection of sustainable building materials by construction industry stockholders and identified that the perception of extra cost and the lack of information on the materials are the main obstacles for sustainable materials selection. Vinodh et al. [17] has carried out a case study on sustainable concept selection and pointed out that TOPSIS is the suitable MCDM technique for sustainable concept selection. The Fuzzy Extended Analytical Hierarchy Process (FEAHP) based sustainable material selection model is proposed by Akadiri et al. [18]. Dursun and Arslan [19] proposed an integrated decision framework for material selection procedure considering quality function deployment (QFD), 2-tuple fuzzy linguistic representation, and linguistic hierarchies. Zhang et al. [20] proposed a hybrid MCDM method combining decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA), and TOPSIS to the strategy selection of material for promoting sustainability development. Based on the above literature review, it is found that the applications of MCDM for the selection of sustainable construction materials, especially siliceous concrete materials, for construction industry are exceedingly scarce. The management of a vast number of siliceous concrete materials with a sustainable concept should be based on clearly defined sustainable indicators related to technical, environmental, and socio-economic issues. Therefore, the present research objective is to implement the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for orderly management of siliceous materials based on sustainable criteria, namely, technical, environmental, social and economic aspects and to promote sustainable development. Appl. Sci. 2019, 9, 3457 3 of 15 2. Materials and Methods 2.1. Selection of Sustainability Evaluation Indicators The sustainability indicators satisfying technical, environmental, and socio-economic criteria are framed to evaluate the sustainable management of siliceous concrete manufacturing material. Sustainability can be enhanced by considering indicators based on environmental, social, and economic aspects. In the present research, wide spectrums of indicators have been employed. In the ranking of siliceous concrete materials, the current model adopts eight, six, and three each of technical, environmental, social, and economic situations indices, respectively. The selected technical sustainability indices for concrete siliceous material includes siliceous material availability, relative proportion of concrete components, consistency of concrete mix, concrete compaction system, cohesiveness of concrete mix, concrete curing system, comply strength requirement of concrete mix, and comply durability requirements of concrete mix. The sustainability indicators for the selection of concrete siliceous material to attain environmental objectives include waste material utilization, concrete material conservation, reduction in carbon footprint, resistance to extreme exposure conditions, and energy conservation conformation to environmental standards. The sustainability indicators for concrete siliceous material to meet socio-economic objectives are considered as public welfare and safety, waste material cleaning, increased employment, life-long maintenance cost, concrete production cost, and siliceous material transportation cost. The Siliceous Concrete Materials Management for Sustainability approach is considered as a way for the concrete construction industry to move towards achieving sustainable development taking into account technical, environmental, socio and economic issues, as shown in Table 1. Sustainable materials management is also a way to portray the construction industry’s responsibility towards protecting the environment [21–24]. The practice of sustainable Siliceous Concrete Materials management refers to a process to develop construction industry that causes less harm to the environment—i.e., reducing the natural resources using basic construction materials and waste material management, reducing the environmental burdens of basic construction materials, reducing energy consumption in construction activities, reducing the burden on non-renewable construction materials; increasing durability against extreme exposure conditions; the use of standard recycled/sustainability sourced products, beneficial to the society, and profitable to the conduction industries. Material construction practitioners around the world are beginning to appreciate sustainability and recognize the benefits of implementing sustainable principles in concrete construction. The idea of sustainable materials, for instance, costs less than conventional materials and saves energy. Sustainable concrete material will make a positive contribution to improving quality of life, work eciency and a good working atmosphere. 2.2. Fuzzy TOPSIS Methodology Zadeh [25] implemented the concept of fuzzy sets theory to express the linguistic terms used in decision-making to alleviate the diculty of operational management. Hwang and Yoon [26] first suggested the TOPSIS method, a linear weighting technique. The weights can be assigned to the criteria using various methods such as mean weight (MW), entropy analysis, eigenvector method, standard deviation (SD), analytical network process (ANP), and analytical hierarchy process (AHP). The proposed MCDM based Fuzzy TOPSIS approach is implemented to the problem of ranking the sustainable concrete siliceous material. Based on an in-depth literature review, eleven of the most common siliceous concrete materials were identified. It includes Nano-Cement, Nano-Particles of Siliceous Material, Natural Pozzolana, Metakaolin, Silica Fume, Fly Ash, Rice Husk Ash, Lime Stone, Blast Furnace Slag, Recycled Aggregate, and Waste Glass. Figure 1 illustrates the fuzzy-TOPSIS based framework for the ranking of sustainable siliceous concrete materials management. Appl. Sci. 2019, 9, 3457 4 of 15 Appl. Sci. 2019, 9, x FOR PEER REVIEW 4 of 17 Figure 1. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS) based Figure 1. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS) framework for ranking of sustainable siliceous concrete material management. based framework for ranking of sustainable siliceous concrete material management. Table 1. Sustainable criteria along with sustainability indicators (sub-criteria) for selection of siliceous The experts with commendable experience in concrete technology were asked to judge and rank concrete materials and their principal issues. the selected sustainable criteria and sustainable indicators. A questionnaire (Sample Questionnaire- Title Sustainability Criteria Principal Issues 1, Appendix A) based on linguistics terms and triangular fuzzy number (TFN) was offered for siliceous material availability establishing the importance of the criteria and role of siliceous concrete material towards relative proportion of sustainability. Questionnaire-1 used five linguistic terms [27], namely, Very Low, Low, Medium, concrete components High, and Very High, along with corresponding triangular fuzzy numbers (TFN) of (0,0.1,0.3), consistency of concrete mix properly managed construction materials utilization; protection concrete compaction system (0.1,0.3,0.5), (0.3,0.5,0.7), (0.5,0.7,0.9), and (0.7,0.9,1), respectively, reflecting the importance weights technical of sensitive ecosystems through good construction practices and Cohesiveness of concrete mix sustainability supervision; technically proven high preformation construction of each performance criteria in providing sustainability in siliceous concrete material. Later, on Concrete curing system materials; low water consumption during production. Questionnaire-2 (Append  Comply ix B) w strength as administered which used five linguistic terms [28], namely, Very requirement of concrete mix Poor, Poor, Fair, Good and Very Good, along with corresponding triangular fuzzy numbers (TFN) of Comply durability (0,1,3), (1,3,5), (3,5,7), (5,7,9), and (7,9,10) to ascertain the role of each concrete siliceous material to requirements of concrete mix provide the much needed sustainability on the selected set of twenty criteria. The overall performance Waste material utilization Reduction of natural resources using basic construction Concrete of each concrete siliceous material was documented. In order to find the preferential sustainable materials and waste material management; reduction of the material conservation concrete siliceous material, the selected criteria were further utilized to rate the performance of each Environmental  Reduction in carbon environmental burdens of basic construction materials; preferent sustainability ial concrete foot siliprint ceous material using Ze reduction leny’s [ of2ener 9] opin gy consumption ion. Accor in dconstr ing to uction Hwang activities; and Yoon Resistance to extreme reduction of the burdens on non-renewable construction [26], in comparison with others, the selected option should have the optimal distance (most close to exposure conditions materials; increased durability against extreme exposure positive and farthest from adverse) i.e., alternatives should not only be the shortest distance from the Energy conservation conditions; use of standard recycled/sustainability Conformation to sourced products. positive ideal reference point (PIRP) but also the longest distance from the negative ideal reference environmental standards point (NIRP). The algorithm used in this method is described in the following section. Health, safety and conducive working environment; minimizing Public welfare and safety local nuisance and disruption; contributing to the local economy Social Table 1. Sustainable criteria along with sustainability indicators (sub-criteria) for selection of siliceous through local employment and procurement; building long-term Waste material cleaning sustainability relationships with local suppliers; minimizing strain on land concrete materi  als and Increased their pr employment incipal issues. resources and improving of overall quality of life. Sustainability Improved productivity; employee economic satisfaction; lower Title Principal Issues Life-long maintenance cost cost projects with increased cost predictability; delivering Criteria Economic  Concrete production cost services that provide best value to clients; supplier satisfaction; • siliceous material sustainability client satisfaction with minimum defects; low cost maintenance; Siliceous material availability low cost product through minimum transportation cost; transportation cost optimized life-cycle economic performance. • relative properly managed construction materials utilization; proportion of concrete protection of sensitive ecosystems through good technical The experts with components commendable experience construction practices in concrete technology and supervision were asked to ; te judge chnically and rank sustainability • consistency of proven high preformation construction materials; low the selected sustainable criteria and sustainable indicators. A questionnaire (Sample Questionnaire-1, Appendix A) based concrete mix on linguistics terms and water consumption durin triangular fuzzy number g product (TFN) ion. was o ered for • concrete compaction system Appl. Sci. 2019, 9, 3457 5 of 15 establishing the importance of the criteria and role of siliceous concrete material towards sustainability. Questionnaire-1 used five linguistic terms [27], namely, Very Low, Low, Medium, High, and Very High, along with corresponding triangular fuzzy numbers (TFN) of (0,0.1,0.3), (0.1,0.3,0.5), (0.3,0.5,0.7), (0.5,0.7,0.9), and (0.7,0.9,1), respectively, reflecting the importance weights of each performance criteria in providing sustainability in siliceous concrete material. Later, on Questionnaire-2 (Appendix B) was administered which used five linguistic terms [28], namely, Very Poor, Poor, Fair, Good and Very Good, along with corresponding triangular fuzzy numbers (TFN) of (0,1,3), (1,3,5), (3,5,7), (5,7,9), and (7,9,10) to ascertain the role of each concrete siliceous material to provide the much needed sustainability on the selected set of twenty criteria. The overall performance of each concrete siliceous material was documented. In order to find the preferential sustainable concrete siliceous material, the selected criteria were further utilized to rate the performance of each preferential concrete siliceous material using Zeleny’s [29] opinion. According to Hwang and Yoon [26], in comparison with others, the selected option should have the optimal distance (most close to positive and farthest from adverse) i.e., alternatives should not only be the shortest distance from the positive ideal reference point (PIRP) but also the longest distance from the negative ideal reference point (NIRP). The algorithm used in this method is described in the following section. 2.2.1. Construction of the Fuzzy Decision Matrix for Sustainability Problem Given m alternatives for sustainable concrete siliceous material, n selection criteria, and k expert group of professionals, a typical fuzzy decision matrix for sustainability problem can be expressed as below: 1 2 n SC SC :::::: SC 2 3 a a a 6 11 12 1n 7 6 7 6  7 6 7 6 7 a a a 6 22 2n 7 A (1) 2 6 7 e 6 7 D= , i = 1, 2,:::::: , m; j = 1, 2, :::::: , n 6 7 . . . 6 . 7 6 . . . . 7 6 . 7 . . . 6 7 6 7 4 5 a a  a n1 n2 nn where A , A , ::: , A are the alternatives materials to be chosen, SC , SC , ::: , SC denote the n n 1 2 1 2 sustainability evaluation criteria for concrete siliceous material, D represents the rating of alternative ij materials A with respect to sustainability criterion SC evaluated by k experts. Since the perception i j toward ranking the sustainable concrete siliceous material is subject to an individual’s experience, intuition, or knowledge, this study, therefore, uses the technique of average value to integrate the fuzzy performance score e x for k experts concerning the same evaluation criteria, that is ij 1 2 k e x = (e x + e x + ::: + e x (2) ij ij ij ij where e x is the rating of alternative Ai with respect to criterion SCj evaluated by the k expert and ij k k k k e x = a , b , c . (3) ij ij ij ij 2.2.2. Normalization of the Fuzzy Decision Matrix for Sustainability Problem The various criteria required to select the sustainable concrete siliceous material are measured in di erent units and therefore need to be normalized. The current study adopts linear scales to transform the normalization function for preserving the property of the ranges of normalized TFN to be included in [0, 1]. If R denotes the normalized fuzzy decision matrix, then h i R= e r , I = 1, 2,:::::: , m; j = 1, 2, :::::: , n (4) ij mxn Appl. Sci. 2019, 9, 3457 6 of 15 a b c ij ij ij where r = , , ij + + + sc sc sc j j j SC = maxSC (5) ij 2.2.3. Construction of Weighted Normalized Fuzzy Decision Matrix for Sustainability Problem Considering the di erent weight of each sustainability criterion, the weighted normalized decision matrix can be computed by multiplying the importance weights of the evaluation criteria and the values in the normalized fuzzy decision matrix. The weighted normalized decision matrix e v is defined as h i e= e , i = 1, 2,:::::: , m; j = 1, 2, :::::: , n (6) ij mxn e e = r w (7) ij ij j where w represents the importance weight of criterion C obtained through j j 1 2 k e e e e w = w + w + ::: + w (8) j j j where k is the number of expert members in a group and w e represents the fuzzy weight of j criteria assessed by kth expert” 2.2.4. Determination of the FPIRP and FNIRP The fuzzy negative ideal reference point (FNIRP, A ) and fuzzy positive ideal reference point (FPIRP, A ) in the interval [0, 1] can be represented as: + + + + e e e A =  ,  ,::: (9) 1 2 A = e , e ,:::e (10) 1 2 e e where  = (1, 1, 1) and  = (0, 0, 0), j = 1, 2, ::: ..,n j j 2.2.5. Calculation for the Distances of Each Concrete Siliceous Material to FPIRP and FNIRP The distance of each concrete siliceous material alternate from the fuzzy positive ideal reference point (FPIRP) and the fuzzy negative ideal reference point (FNIRP) can be derived respectively as + + d = d(e , e ), i = 1, 2,:::::: , n; j = 1, 2, :::::: , n (11) ij i j j=1 e e d = d( ,  ), i = 1, 2,:::::: , m; j = 1, 2, :::::: , n (12) ij i j j=1 e e where, d  ,  , denotes the distance measurement between two fuzzy numbers, d represents the ij j distance of alternative L from FPIRP, and d is the distance of alternative L from FNIRP. i i 2.2.6. Process to Obtain the Closeness Coecient and Rank the Order of Alternatives Once the closeness coecient (CC) is determined, the ranking order of all alternatives can be obtained, allowing the decision-makers to select the most feasible alternative. The closeness coecient of each alternative is calculated as cc = i = 1, 2, 3, :::::: m (13) d + D i i Appl. Sci. 2019, 9, 3457 7 of 15 An option with index cc approaching 1 shows that the option is near to the fuzzy positive ideal reference point and far from the fuzzy negative ideal reference point. A large proximity index value indicates a good performance of the option Ai. 2.2.7. Assessment of Sustainable Concrete Siliceous Material The ranking of concrete siliceous materials with sustainability objectives is a multi-criteria decision-making process. After the initial problem formulation, expert advice and opinion may be sought to determine the sustainable assessment criteria and indicators. Experts may employ their vast experience and expertise while ranking concrete siliceous material according to their merits in sustainability. The use of linguistic terms and corresponding TFN will help to make their decision in fuzzy based assessment. The fuzzy TOPSIS methodology was employed. The five experts were asked to judge the role of the criteria in providing sustainability. They were also asked to judge the role of each concrete siliceous material in providing sustainability. The detailed methodology adopted in ranking the concrete siliceous material, as per the closeness to sustainability goals, is documented in the following section. 3. Results 3.1. Calculation of the Synthetic Importance Weights of Evaluation Criteria The expert group expressed their opinion in linguistics terms for their preference of sustainability evaluation indicators [27], namely Very Low, Low, Medium, High, and Very High, corresponding to its TFN. An integrated fuzzy importance weight matrix for evaluation criteria was generated using the method of average value described in Equation (7). To understand the importance order of these selection criteria, the center of area (COA) method [30] was utilized to de-fuzzify TFN into corresponding best non-fuzzy performance (BNP) values. The twenty most important sustainable indicators for assessing concrete siliceous materials for sustainability with corresponding BNP values are presented in Table 2 as SC (0.66), SC (0.72), SC (0.70), SC (0.7267), SC (0.76), SC (0.72), SC 1 2 3 4 5 6 7 (0.6867), SC (0.42), SC (0.7667), SC (0.8667), SC (0.80), SC (0.7667), SC (0.7333), SC (0.7667), 8 9 10 11 12 13 14 SC (0.4133), SC (0.3933), SC (0.38), SC (0.4267), SC (0.40), and SC (0.46). The maximum BNP 15 16 17 18 19 20 value was obtained for the sustainable indicator of “concrete material conservation (SC )”, while the minimum BNP value was obtained for the sustainable indicator of “increased employment (SC )”. 3.1.1. Construction of the Fuzzy Decision Matrix The ranking of concrete siliceous materials is an important issue for sustainable concrete objectives. In order to accomplish sustainability goals, a systematic performance analysis of various sustainability criteria and their indicators was carried out. The experts gave their feedback in linguistic terms. The experts used the linguistic terms Very Poor, Poor, Fair, Good and Very Good along with TFN, as depicted in Appendix A, to express their opinions for each concrete siliceous material based on their individual capability against each sustainability evaluation indicator. The fuzzy performance ratings of each concrete siliceous material regarding evaluation indicators were averaged to synthesize the various individual judgments. With Equation (1), the synthetic fuzzy decision matrix can be computed, as shown in Table 3. Fuzzy weights were obtained after normalizing the BNP values. Appl. Sci. 2019, 9, 3457 8 of 15 Table 2. Fuzzy importance weight, best non-fuzzy performance (BNP), and rank of each indicator. Indicator Description of the Indicator Fuzzy Importance Weight BNP Values Rank SC Concrete curing system (0.460,0.660,0.860) 0.6600 13 SC Concrete compaction system (0.540,0.740,0.880) 0.7200 9 SC Cohesiveness of concrete mix (0.500,0.700,0.900) 0.7000 11 SC Consistency of concrete mix (0.540,0.740,0.900) 0.7267 8 SC Comply strength requirement of concrete mix (0.580,0.780,0.920) 0.7600 6 SC Comply durability requirements of concrete mix (0.5400.740,0.880) 0.7200 9 SC Relative proportion of concrete components (0.500,0.700,0.860) 0.6867 12 SC Siliceous material availability (0.220,0.420,0.620) 0.4200 16 SC Energy conservation (0.580,0.780,0.940) 0.7667 3 SC Concrete material conservation (0.700,0.900,1.000) 0.8667 1 SC Waste material utilization (0.620,0.820,0.960) 0.8000 2 SC Conformation to environmental standards (0.580,0.780,0.940) 0.7667 5 SC Reduction in carbon foot print (0.540,0.740,0.920) 0.7333 7 SC Resistance to extreme exposure conditions (0.580,0.780,0.940) 0.7667 3 SC Waste material cleaning (0.220,0.420,0.600) 0.4133 17 SC Public welfare and safety (0.240,0.380,0.560) 0.3933 19 SC Increased employment (0.220,0.420,0.500) 0.3800 20 SC Concrete production cost (0.240,0.420,0.6200 0.4267 15 SC Siliceous material transportation cost (0.240,0.400,0.560) 0.4000 18 SC Lifelong maintenance cost (0.260,0.460,0.660) 0.4600 14 3.1.2. Calculation of Normalized Fuzzy Decision Matrix and Weighted Normalized Matrix To ensure that the normalized triangular fuzzy numbers are included in the interval [0, 1], the linear scale transforms function is used. The synthetic fuzzy decision matrices were normalized using the Equations (2)–(4), and the results are shown in Table 4. Normalization process was carried out by dividing each row by the maximum of that row. The normalized values are shown in the table. The normalized fuzzy numbers were later applied on importance weights and since the importance weights of criteria are di erent, Equations (6) and (7) was employed for the fuzzy weighted normalized decision matrix, results are shown in Table 5. 3.1.3. Determination of the Fuzzy Positive and Fuzzy Negative Ideal Reference Points As the positive TFN are in the range of [0, 1], so the fuzzy positive ideal reference point and fuzzy negative ideal reference point can be defined as A = [(1, 1, 1), (1, 1, 1), (1, 1, 1), (1, 1, 1), (1, 1, 1)] (14) A = [(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0)] (15) 3.1.4. Calculation for the Distance of Each Concrete Siliceous Material to FPIRP and FNIRP and Determining the Closeness Coecient (CC) for Ranking of Concrete Siliceous Material The distance of each concrete siliceous material to the FPIRP and FNIRP can be calculated using Equations (10) and (11). Once the distances of concrete siliceous material from FPIRP and FNIRP are determined, the closeness coecient for the concrete siliceous material alternatives can be obtained with Equation (12). Closeness coecients are calculated based on the obtained FPIRP and FNIRP. The distances of concrete siliceous material from FPIRP and FNIRP, the closeness coecient and ranking of various concrete siliceous materials are shown in Table 6. Figure 2 depicts the graphical representation of concrete siliceous materials ranking as per the obtained Closeness Coecients. Appl. Sci. 2019, 9, 3457 9 of 15 Table 3. The fuzzy decision matrix of sustainable siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (3.400,5.400,7.400 (0.600,2.200,4.200) (0.800,2.600,4.600) 2.600,4.600,6.600) (0.800,2.600,4.600) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.200,4.200,6.200) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (1.000,3.000,5.000 (2.600,4.600,6.600) (0.600,2.200,4.200) 2.200,4.200,6.200) (1.000,3.000,5.000) (0.400,1.800,3.800) (2.600,4.600,6.600) (2.800,4.600,6.600) (0.400,1.800,3.800) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (1.400,3.400,5.400) (2.200,4.200,6.200) (2.600,4.600,6.600) 3.000,5.000,7.000) (0.800,2.600,4.600) (2.600,4.600,6.600) (3.000,5.000,7.000) (2.600,4.600,6.600) (2.400,4.200,6.200) (3.000,5.000,7.000) (3.000,5.000,7.000) SC (1.000,3.000,5.000) (4.600,6.600,8.600) (2.200,4.200,6.200) 1.000,3.000,5.000) (1.400,3.400,5.400) (2.600,4.600,6.600) (6.200,8.200,9.600) (3.000,5.000,7.000) (1.800,3.800,5.800) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (1.000,3.000,5.000) (0.800,2.400,4.000) (4.600,6.600,8.600) 3.800,5.800,7.800) (0.600,1.800,3.800) (0.200,1.400,3.400) (3.800,5.800,7.800) (4.600,6.600,8.600) (0.200,1.400,3.400) (0.200,1.400,3.400) (0.200,1.400,3.400) SC 0.200,1.200,3.400) (0.600,2.200,4.200) (0.800,2.400,4.600) 2.400,4.000,5.600) (0.000,0.800,2.400) (0.200,1.200,3.800) (2.400,4.000,5.600) (1.600,3.200,5.400) (0.200,1.200,2.800) (0.200,1.200,2.800) (0.200,1.200,2.800) SC (0.200,1.400,3.400) (2.600,4.600,6.600) (0.600,2.200,4.200) 3.000,5.000,7.000) (0.000,1.000,3.000) (2.600,4.600,6.600) (3.000,5.000,7.000) (0.600,2.200,4.200) (1.000,2.600,4.600) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.200,1.400,3.400) (2.200,4.200,6.200) (2.600,4.600,6.600) 1.800,3.800,5.800) (0.000,1.000,3.000) (2.600,4.600,6.600) (6.200,8.200,9.600) (3.400,5.400,7.400) (1.600,3.400,5.400) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.000,1.000,3.000) (4.000,5.800,7.800) (2.200,4.200,6.200) 1.800,3.800,5.800) (0.000,1.000,3.000) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.600,4.600,6.600) (0.000,1.000,3.000) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (0.200,1.400,3.400) (4.000,5.800,7.800) (4.000,5.800,7.800) 2.600,4.600,6.600) (1.000,3.000,5.000) (0.400,1.800,3.800) (2.600,4.600,6.600) (4.000,5.800,7.800) (0.200,1.400,3.400) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (0.000,1.000,3.000) (0.800,2.600,4.600) (0.800,2.600,4.600) 1.400,3.400,5.400) (1.000,3.000,5.000) (2.600,4.600,6.600) (3.000,5.000,7.000) (2.000,3.800,5.800) (1.000,2.600,4.600) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (0.400,1.800,3.800) (2.600,4.600,6.600) (0.800,2.600,4.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (2.600,4.600,6.600) (6.200,8.200,9.600) (0.400,1.800,3.800) (1.200,3.000,5.000) (2.600,4.600,6.600) (2.600,4.600,6.600) SC (1.000,3.000,5.000) (2.600,4.600,6.600) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.200,3.000,5.000) (4.600,6.600,8.600) (6.600,8.600,9.800) (2.600,4.600,6.600) (4.200,6.200,8.200) (4.600,6.600,8.600) (4.600,6.600,8.600) SC (1.000,3.000,5.000) (4.200,6.200,8.200) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (1.400,3.400,5.400) (3.400,5.400,7.400) (4.200,6.200,8.200) (1.000,3.000,5.000) (1.400,3.400,5.400) (1.400,3.400,5.400) SC (1.800,3.800,5.800) (2.600,4.600,6.600) (4.200,6.200,8.200) 1.800,3.800,5.800) (1.000,3.000,5.000) (0.800,2.600,4.600) (3.800,5.800,7.800) (2.600,4.600,6.600) (1.800,3.800,5.800) (0.800,2.600,4.600) (0.800,2.600,4.600) SC (2.200,4.200,6.000) (4.600,6.600,8.600) (2.600,4.600,6.600) 2.200,4.200,6.000) (1.000,3.000,5.000) (0.400,1.800,3.800) (5.400,7.400,9.200) (1.800,3.800,5.800) (1.800,3.400,5.200) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (1.800,3.800,5.800) (2.600,4.600,6.600) (1.400,3.400,5.400) 2.600,4.600,6.600) (1.000,3.000,5.000) (0.400,1.800,3.800) (3.400,5.400,7.400) (2.600,4.600,6.600) (1.200,2.600,4.600) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (3.400,5.400,7.400) (4.600,6.600,8.600) (2.600,4.600,6.600) 1.800,3.800,5.800) (1.000,3.000,5.000) (0.200,1.400,3.400) (3.800,5.800,7.800) (2.600,4.600,6.600) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) SC (3.800,5.800,7.800 (4.600,6.600,8.600) (1.400,0.400,5.400) 1.800,3.800,5.800) (1.400,3.400,5.400) (0.400,1.800,3.800) (3.800,5.800,7.800) (2.200,4.200,6.200) (1.400,3.000,5.000) (0.400,1.800,3.800) (0.400,1.800,3.800) SC (5.400,7.400,9.200) (0.600,2.200,4.200) (1.800,3.800,5.800) 5.400,7.400,9.200) (1.800,3.800,5.800) (0.200,1.400,3.400) (5.400,7.400,9.200) (2.200,4.200,6.200) (1.200,2.600,4.600) (0.200,1.400,3.400) (0.200,1.400,3.400) Table 4. The fuzzy normalized decision matrix of sustainable siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (0.436,0.692,0.949) (0.103,0.333,0.590) (0.103,0.333,0.590) (0.333,0.590,0.846) (0.103,0.333,0.590) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.282,0.538,0.795) (0.154,0.333,0.590) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.152,0.455,0.758) (0.091,0.333,0.636) (0.091,0.333,0.636) (0.333,0.636,0.939) (0.152,0.455,0.758) (0.061,0.273,0.576) (0.394,0.697,1.000) (0.424,0.697,1.000) (0.061,0.273,0.576) (0.061,0.273,0.576) (0.061,0.273,0.576) SC (0.200,0.486,0.771) (0.371,0.657,0.943) (0.371,0.657,0.943) (0.429,0.714,1.000) (0.114,0.371,0.657) (0.371,0.657,0.943) (0.429,0.714,1.000) (0.371,0.657,0.943) (0.343,0.600,0.886) (0.429,0.714,1.000) (0.429,0.714,1.000) SC (0.104,0.313,0.521) (0.229,0.438,0.646) (0.229,0.438,0.646) (0.104,0.313,0.521) (0.146,0.354,0.563) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.313,0.521,0.729) (0.188,0.396,0.604) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.116,0.349,0.581) (0.535,0.767,1.000) (0.535,0.767,1.000) (0.442,0.674,0.907) (0.070,0.209,0.442) (0.023,0.163,0.395) (0.442,0.674,0.907) (0.535,0.767,1.000) (0.023,0.163,0.395) (0.023,0.163,0.395) (0.023,0.163,0.395) SC (0.036,0.214,0.607) (0.143,0.429,0.714) (0.143,0.429,0.821) (0.429,0.714,1.000) (0.000,0.143,0.429) (0.036,0.214,0.679) (0.429,0.714,1.000) (0.286,0.571,0.964 (0.036,0.214,0.500) (0.036,0.214,0.500) (0.036,0.214,0.500) SC (0.029,0.200,0.486) (0.086,0.314,0.600) (0.086,0.314,0.600) (0.429,0.714,1.000) (0.000,0.143,0.429) (0.371,0.657,0.940) (0.429,0.714,1.000) (0.086,0.314,0.600) (0.143,0.371,0.657) (0.371,0.657,0.943) (0.371,0.657,0.943) SC (0.021,0.146,0.354) (0.271,0.479,0.688) (0.271,0.479,0.688) (0.188,0.396,0.604) (0.000,0.104,0.313) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.354,0.563,0.771) (0.167,0.354,0.563) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.000,0.128,0.385) (0.282,0.538,0.795) (0.282,0.538,0.795) (0.231,0.487,0.744) (0.000,0.128,0.385) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.333,0.590,0.846) (0.000,0.128,0.385) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.026,0.179,0.436) (0.513,0.744,1.000) (0.513,0.744,1.000) (0.333,0.590,0.846) (0.128,0.385,0.641) (0.051,0.231,0.487) (0.333,0.590,0.846) (0.513,0.744,1.000) (0.026,0.179,0.436) (0.051,0.231,0.487) (0.051,0.231,0.487) SC (0.000,0.128,0.385) (0.513,0.744,1.000) (0.103,0.333,0.590) (0.179,0.436,0.692) (0.128,0.385,0.641) (0.333,0.590,0.846) (0.385,0.641,0.897) 90.256,0.487,0.744 (0.128,0.333,0.590) (0.333,0.590,0.846) (0.333,0.590,0.846) SC (0.042,0.188,0.396) (0.083,0.271,0.470) (0.083,0.271,0.479) (0.188,0.396,0.604) (0.104,0.313,0.521) (0.271,0.479,0.688) (0.646,0.854,1.000) (0.042,0.188,0.396) (0.125,0.313,0.521) (0.271,0.479,0.688) (0.271,0.479,0.688) SC (0.102,0.306,0.510) (0.265,0.469,0.673) (0.265,0.469,0.673) (0.184,0.388,0.592) (0.122,0.306,0.510) (0.469,0.673,0.878) (0.673,0.878,1.000) (0.265,0.469,0.673) (0.429,0.633,0.837) (0.469,0.673,0.878) (0.469,0.673,0.878) SC (0.135,0.405,0.676) (0.351,0.622,0.892) (0.351,0.622,0.892) (0.243,0.514,0.784) (0.135,0.405,0.676) (0.189,0.459,0.730) (0.459,0.730,1.000) (0.351,0.622,0.892) (0.135,0.405,0.676 (0.189,0.459,0.730) (0.189,0.459,0.730) SC (0.220,0.463,0.707) (0.512,0.756,1.000) (0.512,0.756,1.000) (0.220,0.463,0.707) (0.122,0.366,0.610) (0.098,0.317,0.561) (0.463,0.707,0.950) (0.512,0.756,1.000) (0.220,0.463,0.707) (0.098,0.317,0.561) (0.098,0.317,0.561) SC (0.239,0.457,0.652) (0.283,0.500,0.717) (0.283,0.500,0.717) (0.239,0.457,0.652) (0.109,0.326,0.540) (0.043,0.196,0.413) (0.587,0.804,1.000) (0.283,0.500,0.717) (0.196,0.370,0.565) (0.043,0.196,0.413) (0.043,0.196,0.413) SC (0.209,0.442,0.674) (0.535,0.767,1.000) (0.163,0.395,0.628) (0.302,0.535,0.767) (0.116,0.349,0.581) (0.047,0.209,0.442) (0.395,0.628,0.860) (0.209,0.442,0.674) (0.140,0.302,0.535) (0.047,0.209,0.442) (0.047,0.209,0.442) SC (0.436,0.692,0.949) (0.333,0.590,0.846) (0.333,0.590,0.846) (0.231,0.487,0.744) (0.128,0.385,0.641) (0.026,0.179,0.436) (0.487,0.744,1.000) (0.333,0.590,0.846) (0.154,0.333,0.590) (0.026,0.179,0.436) (0.026,0.179,0.436) SC (0.442,0.674,0.907) (0.535,0.767,1.000) (0.163,0.395,0.628) (0.209,0.442,0.674) (0.163,0.395,0.628) (0.047,0.209,0.442) (0.442,0.674,0.907) (0.302,0.535,0.767) (0.163,0.349,0.581) (0.047,0.209,0.442) (0.047,0.209,0.442) SC (0.587,0.804,1.000) (0.500,0.717,0.935) (0.196,0.413,0.630) (0.587,0.804,1.000) (0.196,0.413,0.630) (0.022,0.152,0.370) (0.587,0.804,1.000) (0.239,0.457,0.674) (0.130,0.283,0.500) (0.022,0.152,0.370) (0.022,0.152,0.370) 20 Appl. Sci. 2019, 9, 3457 10 of 15 Table 5. The fuzzy weighted normalized decision matrix of Sustainable Siliceous materials alternatives. Criteria A A A A A A A A A A A 1 2 3 4 5 6 7 8 9 10 11 SC (0.201,0.457,0.816) (0.047,0.220,0.507) (0.047,0.220,0.507) (0.153,0.389,0.728) (0.047,0.220,0.507) (0.012,0.118,0.375) (0.224,0.491,0.860) (0.130,0.355,0.684) (0.071,0.220,0.507) (0.012,0.118,0.375) (0.012,0.118,0.375) SC (0.082,0.336,0.667) (0.049,0.247,0.560) (0.049,0.247,0.560) (0.180,0.471,0.827) (0.082,0.3360.652) (0.033,0.202,0.507) (0.213,0.516,0.880) (0.229,0.516,0.880) (0.033,0.202,0.507) (0.033,0.202,0.507) (0.033,0.202,0.507) SC (0.100,0.340,0.694) (0.186,0.460,0.849) (0.186,0.460,0.849) (0.214,0.500,0.900) (0.057,0.260,0.565) (0.186,0.460,0.849) (0.214,0.500,0.900) (0.186,0.460,0.849) (0.171,0.420,0.797) (0.214,0.500,0.900) (0.214,0.500,0.900) SC (0.056,0.231,0.469) (0.124,0.324,0.581) (0.124,0.324,0.581) (0.056,0.231,0.469) (0.079,0.262,0.484) (0.146,0.355,0.619) (0.349,0.632,0.900) (0.169,0.385,0.656) (0.101,0.293,0.544) (0.146,0.355,0.619) (0.146,0.355,0.619) SC (0.067,0.272,0.535) (0.310,0.599,0.920) (0.310,0.599,0.920) (0.256,0.526,0.834) (0.040,0.163,0.380) (0.013,0.127,0.364) (0.256,0.526,0.834) (0.310,0.599,0.920) (0.013,0.127,0.364) (0.013,0.127,0.364) (0.013,0.127,0.364) SC (0.019,0.159,0.534) (0.077,0.317,0.629) (0.077,0.317,0.723) (0.231,0.529,0.880) (0.000,0.106,0.369) (0.019,0.159,0.597) (0.231,0.529,0.880) (0.154,0.423,0.849) (0.019,0.159,0.440) (0.019,0.159,0.440 (0.019,0.159,0.440) SC (0.014,0.140,0.418) (0.043,0.220,0.516) (0.043,0.220,0.516) (0.214,0.500,0.860) (0.000,0.100,0.369) (0.186,0.460,0.811) (0.214,0.500,0.860) (0.043,0.220,0.516) (0.071,0.260,0.565) (0.186,0.460,0.811) (0.186,0.460,0.811) SC (0.005,0.061,0.220) (0.060,0.201,0.426) (0.060,0.201,0.426) (0.041,0.166,0.375) (0.000,0.044,0.269) (0.060,0.201,0.426) (0.142,0.359,0.620) (0.078,0.236,0.478) (0.037,0.149,0.349) (0.060,0.201,0.426) (0.060,0.201,0.426) SC (0.000,0.100,0.362) (0.164,0.420,0.747) (0.164,0.420,0.747) (0.134,0.380,0.699) (0.000,0.100,0.331) (0.015,0.140,0.410) (0.283,0.580,0.940) (0.193,0.460,0.795) (0.000,0.100,0.362) (0.015,0.140,0.410) (0.015,0.140,0.410) SC (0.018,0.162,0.436) (0.359,0.669,1.000) (0.359,0.669,1.000) (0.233,0.531,0.846) (0.090,0.346,0.551) (0.036,0.208,0.487) (0.233,0.531,0.846) (0.359,0.669,1.000) (0.018,0.162,0.436) (0.036,0.208,0.487) (0.036,0.208,0.487) SC (0.000,0.105,0.369) (0.318,0.610,0.960) (0.064,0.273,0.566) (0.111,0.357,0.665) (0.079,0.315,0.551) (0.207,0.484,0.812) (0.238,0.526,0.862) (0.159,0.399,0.714) (0.079,0.273,0.566) (0.207,0.484,0.812) (0.207,0.484,0.812) SC (0.024,0.146,0.372) (0.048,0.211,0.450) (0.048,0.211,0.450) (0.109,0.309,0.568) (0.060,0.244,0.448) (0.157,0.374,0.646) (0.375,0.666,0.940) (0.024,0.146,0.372) (0.073,0.244,0.490) (0.157,0.374,0.646) (0.157,0.374,0.646) SC (0.055,0.227,0.469) (0.143,0.347,0.620) (0.143,0.347,0.620) (0.099,0.287,0.544) (0.066,0.227,0.439) (0.253,0.498,0.807) (0.364,0.649,0.920) (0.143,0.347,0.620) (0.231,0.468,0.770) (0.253,0.498,0.807) (0.253,0.498,0.807) SC (0.078,0.316,0.635) (0.204,0.485,0.838) (0.204,0.485,0.838) (0.141,0.401,0.737) (0.078,0.316,0.581) (0.110,0.358,0.686) (0.266,0.569,0.940) (0.204,0.485,0.838) (0.078,0.316,0.635) (0.110,0.358,0.686) (0.110,0.358,0.686) SC (0.048,0.195,0.424) (0.113,0.318,0.600) (0.113,0.318,0.600) (0.048,0.195,0.424) (0.027,0.154,0.524) (0.021,0.133,0.337) (0.102,0.297,0.571) (0.113,0.318,0.600) (0.048,0.195,0.424) (0.021,0.133,0.337) (0.021,0.133,0.337) SC (0.057,0.173,0.365) (0.068,0.190,0.402) (0.068,0.190,0.402) (0.057,0.173,0.365) (0.026,0.124,0.467) (0.010,0.074,0.231) (0.141,0.306,0.560) (0.068,0.190,0.402) (0.047,0.140,0.317) (0.010,0.074,0.231) (0.010,0.074,0.231) SC (0.046,0.186,0.337) (0.118,0.322,0.500) (0.036,0.166,0.314) (0.067,0.225,0.384) (0.026,0.147,0.500) (0.010,0.088,0.221) (0.087,0.264,0.430) (0.046,0.186,0.337) (0.031,0.127,0.267) (0.010,0.088,0.221) (0.010,0.088,0.221) SC (0.105,0.291,0.588) (0.080,0.248,0.525) (0.080,0.248,0.525) (0.055,0.205,0.461) (0.031,0.162,0.551) (0.006,0.075,0.270 (0.117,0.312,0.620) (0.080,0.248,0.525) (0.037,0.140,0.366) (0.006,0.075,0.270) (0.006,0.075,0.270) SC (0.106,0.270,0.508) (0.128,0.307,0.560) (0.039,0.158,0.352) (0.050,0.177,0.378) (0.039,0.158,0.540) ((.011,0.084,0.247 (0.106,0.270,0.508) (0.073,0.214,0.430) (0.039,0.140,0.326) (0.011,0.084,0.247) (0.000,0.084,0.247) SC (0.153,0.370,0.660) (0.130,0.330,0.617) (0.051,0.190,0.416) (0.153,0.370,0.660) (0.051,0.190,0.542) 0(.006,0.070,0.244 (0.153,0.370,0.660) (0.062,0.210,0.445) (0.034,0.130,0.330) (0.006,0.070,0.244) (0.006,0.070,0.244) 20 Appl. Sci. 2019, 9, 3457 11 of 15 Table 6. The fuzzy positive ideal reference point (FPIRP) and fuzzy negative ideal reference point (FNIRP) distances, closeness coecients and rank of each sustainable siliceous materials. + - d d Supplementary Material Alternatives cc Ranking i i Limestone A 15.2620 6.3464 0.2937 9 Blast Furnace Slag A 13.2325 8.6205 0.3945 3 Metakaolin A 13.8836 7.9110 0.3630 5 Fly Ash A 13.3874 8.4508 0.3870 4 Rise Husk Ash A 15.6305 6.0714 0.2798 10 Silica Fume A 15.1549 6.4536 0.2987 6 Appl. Sci. 2019, 9, x FOR PEER REVIEW 2 of 17 Nano-Cement A 11.3468 10.790 0.4874 1 Nano-Particles Supp. Mat. A 13.2058 8.6757 0.3965 2 Recycled Aggregate A9 15.4692 6.0042 0.2796 11 Recycled Aggregate A 15.4692 6.0042 0.2796 11 Waste Glass A 15.1564 6.4067 0.2971 7 Waste Glass A10 15.1564 6.4067 0.2971 7 Natural Pozolona A 15.1606 6.4065 0.2971 8 Natural Pozolona A11 15.1606 6.4065 0.2971 8 0.6 0.5 0.4 0.3 0.2 0.1 Figure 2. Ranking of each alternative material based on closeness coecient. Figure 2. Ranking of each alternative material based on closeness coefficient. 4. Discussion 4. Discussion The Fuzzy-TOPSIS based approach has been implemented to manage the use of siliceous concrete The Fuzzy-TOPSIS based approach has been implemented to manage the use of siliceous materials for sustainable development. Mahmoudkelaye et al. [21] applied the Analytic Network concrete materials for sustainable development. Mahmoudkelaye et al. [21] applied the Analytic Process (ANP) as a multi-criteria decision-making method for sustainable material selection for Network Process (ANP) as a multi-criteria decision-making method for sustainable material selection building, considering the holistic impact of materials on the environment through sustainable criteria for building, considering the holistic impact of materials on the environment through sustainable which are marked as economic, technical, socio-cultural, and environmental factors. The importance criteria which are marked as economic, technical, socio-cultural, and environmental factors. The of the criteria and sub-criteria in choosing sustainable materials was determined through this model. importance of the criteria and sub-criteria in choosing sustainable materials was determined through Whereas, the present study implements the Fuzzy Technique for Order of Preference by Similarity to this model. Whereas, the present study implements the Fuzzy Technique for Order of Preference by Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) technique, for orderly Similarity to Ideal Solution (TOPSIS) approach, a Multi-Criteria Decision Making (MCDM) management of siliceous materials based on sustainable criteria, namely, technical, environmental, technique, for orderly management of siliceous materials based on sustainable criteria, namely, social and economic aspects and to promote sustainable development. Various sustainable criteria technical, environmental, social and economic aspects and to promote sustainable development. viz. technical, environmental and socio-economical, are considered. It has been observed that, Various sustainable criteria viz. technical, environmental and socio-economical, are considered. It has in accomplishing the sustainable goals for siliceous concrete materials, the environmental criteria play been observed that, in accomplishing the sustainable goals for siliceous concrete materials, the a central role, whereas the social criteria play the minor role. It has also been observed that the most environmental criteria play a central role, whereas the social criteria play the minor role. It has also e ective sustainable indicator for the ranking of siliceous concrete materials is “concrete material been observed that the most effective sustainable indicator for the ranking of siliceous concrete materials is “concrete material conservation”. It indicates that concrete material conservation is a major issue in sustainable material management and the use of siliceous concrete material should be mandatory in the construction industry for sustainable development. The least effective sustainable indicator observed is the “enhanced employment”, and siliceous concrete materials application has no major impact on social development. Among the eleven selected siliceous concrete materials, nano-engineered materials, namely, nano-cement and nano-particles of siliceous material should be given top priority in material management for the manufacturing of sustainable concrete product. The siliceous materials come next for sustainable concrete construction. The recycled material to be used as siliceous concrete materials occupies the lowest rank among the sustainable concrete materials. The ranking of the material in descending order of preference to produce sustainable concrete is: Nano-cement > Nano-particles of siliceous material > Blast Furnace Slag > Fly Ash > CC Limestone 0.2937 Blast Furnace Slag 0.3944 0.3629 Metakaolin 0.3869 Fly Ash 0.2797 Rise Husk Ash Silica Fume 0.2986 Nano-Cement 0.4874 Nano-Particles supp. 0.3964 Mat. 0.2796 Recycled Aggregate Waste glass 0.2971 0.2971 Natural Pozolona Appl. Sci. 2019, 9, 3457 12 of 15 conservation”. It indicates that concrete material conservation is a major issue in sustainable material management and the use of siliceous concrete material should be mandatory in the construction industry for sustainable development. The least e ective sustainable indicator observed is the “enhanced employment”, and siliceous concrete materials application has no major impact on social development. Among the eleven selected siliceous concrete materials, nano-engineered materials, namely, nano-cement and nano-particles of siliceous material should be given top priority in material management for the manufacturing of sustainable concrete product. The siliceous materials come next for sustainable concrete construction. The recycled material to be used as siliceous concrete materials occupies the lowest rank among the sustainable concrete materials. The ranking of the material in descending order of preference to produce sustainable concrete is: Nano-cement > Nano-particles of siliceous material > Blast Furnace Slag > Fly Ash > Metakaolin > Silica Fume > Waste Glass > Natural Pozolona > Lime Stone > Rice Husk Ash > Recycled Aggregate, where ‘>’ represents preference over other concrete material. The corresponding closeness coecients of the eleven siliceous concrete materials are: 0.4874 > 0.3965 > 0.3945 > 0.3870 > 0.3630 > 0.2987 > 0.2971 > 0.2971 > 0.2937 > 0.2798 > 0.2796 where ‘>’ represents the preference over other concrete material. 5. Conclusions The construction industry must look for a sustainability framework to overcome global resources scarcity and environmental impact by adopting sustainable material management in the concrete manufacturing processes. The proper material management is required to select the siliceous material for the production of concrete product from the ever increasing sources of siliceous materials such as industrial waste products, agro-waste products, building recycled material, natural pozolonic material, and siliceous engineered material. The much needed sustainability may be accrued by considering factors related to technique and the environment as well as socio-economic factors while selecting siliceous concrete materials. Concrete manufacturing, through material management, must adapt to environmental friendly material and processes, which should not only be cost-e ective but also provide economic value and safety for society. In the present study, more comprehensive criteria are selected in order to provide sustainability. Moreover, the study adopts twenty sustainability indicators for siliceous concrete materials, thus covering the material management sustainability aspects to a larger extent. It is found from the adopted MCDM approach that among the selected sustainable indicators, the most e ective sustainable indicator for managing siliceous materials is concrete material conservation. The least governing sustainable indicator is enhanced employment. It can be concluded from the study that the large scale use of siliceous concrete materials in construction industry will help in the conservation of basic concrete materials and environmental protection, though it will not have direct impact on social development. The proposed material management model for siliceous materials suggests that the material could be best utilized for sustainable development by the classifying the various siliceous materials into two groups i.e., Group I with CC > 0.35 and Group II with CC < 0.35. The selected siliceous concrete materials, namely, Nano-cement and Nano-particles of siliceous material, Blast Furnace Slag, Fly Ash, and Metakaoline exhibit larger CC value and are hence classified as Group I materials, which possess higher potential of providing sustainability. The siliceous concrete materials of Silica Fume, Waste Glass, Natural Pozolona, Lime Stone, and Rice Husk Ash exhibit lower values of CC, and hence may be regarded as having lower capability towards achieving sustainability in comparison to the Group II. The nano-engineered material, although costly, will prove to be the best material for sustainable concrete construction and development. The current research provides just a preliminary framework for the selection of basic materials for concrete construction in alignment with sustainability. In selecting sustainable siliceous concrete materials, this research has opened opportunities for further research in sustainable materials. The results of this study can be further expanded and modified to achieve the ultimate objective of encouraging and improving sustainable construction methods. The present research will be of great Appl. Sci. 2019, 9, 3457 13 of 15 importance for the concrete industry dealing with concrete manufacturing and to tackle the challenges like increased manufacturing costs, higher concrete performance requirements, and being risk-free to the environment and society. Author Contributions: Conceptualization and formal analysis, I.I.F. and M.A.; methodology, software, and validation, J.M., I.I.F., M.A., J.M.; writing—original draft preparation, I.I.F. and M.A.; writing—review and editing, J.M.; supervision and project administration, I.I.F., M.A.; funding acquisition, M.A. Funding: This research was funded by Deanship of Scientific Research King Khalid University, grant number 172 (1440) and the APC was funded by authors. Acknowledgments: The authors thankfully acknowledge the Deanship of Scientific Research for proving administrative and financial support. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Questionaire for Fuzzy TOPSIS With respect to the overall goal of “Selection of the Sustainable Siliceous Materials” Sample questions included in questionnaire Q1. How importance is the Sustainable Indicator Support for Concrete Curing System in the rating of 1–9 scale? (C ) Q2. What importance do you assign to Sustainable Indicator Support to Concrete Compaction System in the rating of 1–9 scale? (C )? Q3. What importance do you assign to Sustainable Indicator Support to Cohesiveness of Concrete Mix in the rating of 1–9 scale? (C )? Q4. What importance do you assign to Sustainable Indicator Support to Consistency of Concrete Mix in the rating of 1–9 scale? (C )? Q5. What importance do you assign to Sustainable Indicator Comply Strength Requirement of Concrete Mix in the rating of 1–9 scale? (C )? With Respect to Sustainable Importance (or Preference) of Each Criterion Siliceous Materials. Sustainable (0,0.1,0.3) (0.1,0.3,0.5) (0.3,0.5,0.7) (0.5,0.7,0.9) (0.7,0.9,1) Questions Indicator Very Low Low Medium High Very High Q1 C Q2 C Q3 C Q4 C Appendix B Scoring of Alternatives with Respect to Sustainable Indicator for Overall Goal of “Sustainable Siliceous Materials” Q2-1. What scores do you assign to A with reference to Sustainable Indicator Support to Concrete Curing System (C ) in the rating of 1–9 scale? Q2-2. What scores do you assign to A with reference to Sustainable Indicator Support to Concrete Compaction System (C ) in the rating of 1–9 scale? Q2-3. What scores do you assign to A with reference to Sustainable Indicator Support to Cohesiveness of Concrete Mix (C ) in the rating of 1–9 scale? Q2-4. What scores do you assign to A with reference to Sustainable Indicator Support to Consistency of Concrete Mix (C ) in the rating of 1–9 scale? Q2-5. What scores do you assign to A with reference to Sustainable Indicator Comply Strength Requirement of Concrete Mix (C ) in the rating of 1–9 scale? 5 Appl. Sci. 2019, 9, 3457 14 of 15 With Respect to the Sustainable Performance of Each Sustainable Siliceous Materials Siliceous Materials Alternative with Respect to Each Sustainable Indicator Sustainable Sustainable (0,1,3) Very (1,3,5) (5,7,9) (7,9,10) Questions (3,5,7) Fair Indicator Siliceous Materials Poor Poor Good Very Good Q2-1 C A 1 1 Q2-2 C A 2 1 Q2-3 C A 3 1 Q2-4 C A 4 1 Q2-5 C A 5 1 References 1. Babanli, M.B.; Prima, F.; Vermaut, P.; Demchenko, L.D.; Titenko, A.N.; Huseynov, S.S.; Hajiyev, R.J.; Huseynov, V.M. Material Selection Methods: A Review. In Theory and Application of Fuzzy Systems and Soft Computing; Aliev, R.A., Ed.; ICAFS-2018, AISC 896; Springer Nature AG: Geneve, Switzerland, 2019; pp. 929–936. [CrossRef] 2. Zavadskas, E.K.; Kaklauskas, A.; Saparauskas, J. Sustainable urban development and web-based Multiple Criteria Analysis. Found. Civ. Environ. Eng. 2005, 6, 217–226. 3. Stojci ˇ c, ´ M.; Zavadskas, E.K.; Pamucar ˇ , D.; Stevic, ´ Ž.; Mardani, A. Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018. Symmetry 2019, 11, 350. [CrossRef] 4. Rashid, K.; Razzaq, A.; Ahmad, M.; Rashid, T.; Tariq, S. Experimental and analytical selection of sustainable recycled concrete with ceramic waste aggregate. Constr. Build. Mater. 2017, 154, 829–840. [CrossRef] 5. Bhowmik, C.; Gangwar, S.; Bhowmik, S.; Ray, A. Optimum Selection of Energy-Ecient Material: A MCDM-Based Distance Approach. In Soft Computing Applications. Studies in Computational Intelligence; Ray, K., Pant, M., Bandyopadhyay, A., Eds.; Springer: Singapore, 2018; p. 761. 6. Stevic, Z.; Pamucar, D.; Subotic, M.; Antucheviciene, J.; Zavadskas, E.K. The Location Selection for Roundabout Construction Using Rough BWM-Rough WASPAS Approach Based on a New Rough Hamy Aggregator. Sustainability 2018, 10, 2817. [CrossRef] 7. Mathiyazhagan, K.; Gnanavelbabu, A.; Lokesh, P.B. A sustainable assessment model for material selection in construction industries perspective using hybrid MCDM approaches. J. Adv. Manag. Res. 2019, 16, 234–259. [CrossRef] 8. Khoshnava, S.M.; Rostami, R.; Valipour, A.; Ismail, M.; Rahmat, A.R. Rank of green building material criteria based on the three pillars of sustainability using the hybrid multi criteria decision making method. J. Clean. Prod. 2018, 173, 82–99. [CrossRef] 9. Abeysundara, U.G.Y.; Babel, S.; Gheewala, S. A matrix in life cycle perspective for selecting sustainable materials for buildings in Sri Lanka. Build. Environ. 2009, 44–45, 997–1004. [CrossRef] 10. Govindan, K.; Shankar, K.M.; Kannan, D. Sustainable material selection for construction industry—A hybrid multi criteria decision making approach. Renew. Sustain. Energy Rev. 2016, 55, 1274–1288. [CrossRef] 11. Bakhoum, E.; Brown, D. A hybrid approach using for sustainable ranking of structural materials. Int. J. Sustain. Eng. 2013, 6, 212–224. [CrossRef] 12. Arroyo, P.; Tommelein, I.D.; Ballard, G. Selecting Globally Sustainable Materials: A Case Study Using Choosing by Advantages. J. Constr. Eng. Manag. 2015, 142, 05015015. [CrossRef] 13. Rahman, H.A.; Wang, C.; Wood, L.C.; Ebrahimi, M. Integrating and ranking sustainability criteria for housing. Proc. Inst. Civ. Eng. Eng. Sustain. 2017, 169, 3–30. 14. Ahmed, M.; Qureshi, M.N.; Mallick, J.; Kahla, N.B. Selection of Sustainable Supplementary Concrete Materials Using OSM-AHP-TOPSIS Approach. Adv. Mater. Sci. Eng. 2019, 5, 2850480. [CrossRef] 15. Erdogan, S.A.; Saparauskas, J.; Turskis, Z. A Multi-Criteria Decision-Making Model to Choose the Best Option for Sustainable Construction Management. Sustainability 2019, 11, 2239. [CrossRef] 16. Akadiri, P.O. Understanding barriers a ecting the selection of sustainable materials in building projects. J. Build. Eng. 2015, 4, 86–93. [CrossRef] 17. Vinodh, S.; Mulanjur, G.; Thiagarajan, A. Sustainable Concept Selection Using Modified Fuzzy TOPSIS: A Case Study. Int. J. Sustain. Eng. 2013, 6, 109–116. [CrossRef] Appl. Sci. 2019, 9, 3457 15 of 15 18. Akadiri, P.O.; Olomolaiye, P.O.; Chinyio, E.A. Multi-Criteria Evaluation Model for the Selection of Sustainable Materials for Building Projects. Autom. Constr. 2013, 30, 113–125. [CrossRef] 19. Dursun, M.; Arslan, O. An Integrated Decision Framework for Material Selection Procedure: A Case Study in a Detergent Manufacturer. Symmetry 2018, 10, 657. [CrossRef] 20. Zhang, H.; Peng, Y.; Tian, G.; Wang, D.; Xie, P. Green material selection for sustainability: A hybrid MCDM approach. PLoS ONE 2017, 12, e0177578. [CrossRef] 21. Mahmoudkelaye, S.; Azari, K.T.; Pourvaziri, M.; Asadian, E. Sustainable material selection for building enclosure through ANP method. Case Stud. Constr. Mater. 2018, 9, 00200. [CrossRef] 22. Ding, G.K.C. Sustainable construction—The role of environmental assessment tools. J. Environ. Manag. 2008, 86, 451–464. [CrossRef] 23. Abidin, N.Z. Investigating the awareness and application of sustainable construction concept by Malaysian developers. Habitat Int. 2010, 34, 421–426. [CrossRef] 24. Shen, L.; Tam, V.; Tam, L.; Ji, Y. Project feasibility study: The key to successful implementation of sustainable and socially responsible construction management practice. J. Clean. Prod. 2010, 18, 254–259. [CrossRef] 25. Zadeh, L.A. Fuzzy sets. Inf. Control 1965, 8, 338–353. [CrossRef] 26. Hwang, C.L.; Yoon, K. Multiple Attributes Decision Making Methods and Applications, a State-of-the-Art Survey; Taylor & Francis Group: New York, NY, USA, 1981. 27. Wang, M.J.; Chang, T.C. Tool steel materials selection under fuzzy environment. Fuzzy Sets Syst. 1995, 72, 263–270. [CrossRef] 28. Chen, C.T. Extensions of the TOPSIS for group decisi.on-making under fuzzy environment. Fuzzy Sets Syst. 2000, 114, 1–9. [CrossRef] 29. Zeleny, M. A Concept of Compromise Solutions and the Method of the Displaced Ideal. Comput. Oper. Res. 1974, 1, 479–496. [CrossRef] 30. Zhao, R.; Govind, R. Algebraic characteristics of extended fuzzy numbers. Inf. Sci. 1991, 54, 103–130. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Journal

Applied SciencesMultidisciplinary Digital Publishing Institute

Published: Aug 21, 2019

There are no references for this article.