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The robust linear programming technique for multi–dimensional analysis of preferences

The robust linear programming technique for multi–dimensional analysis of preferences The linear programming technique for multi-dimensional analysis of preferences (LINMAP) is one of the noted multi-attributes decision making (MADM) techniques and has been implemented in crisp and fuzzy environments. Robust optimisation attempts to obtain a solution which is feasible in all circumstances arising due to the uncertainty of parameters. The purpose of this study is to extend the LINMAP method for addressing robustness in MADM problems. In this methodology, robust optimisation concepts are used to describe robustness in decision information and decision making processes. Each alternative is evaluated based on its weighted distance to a robust positive ideal solution (RPIS). The RPIS and the robust weights of attributes are estimated using a new robust linear programming technique. Finally, Monte Carlo simulation is applied to test the robustness of the solution. A numerical example is provided to illustrate the effectiveness of the methodology. Keywords: linear programming technique for multi-dimensional analysis of preferences; LINMAP; robust optimisation; uncertainty; multi-attributes decision making; MADM. Copyright © 2015 Inderscience Enterprises Ltd. The robust linear programming technique for multi-dimensional analysis Reference to this paper should be made as follows: Mohammadi-Dehcheshmeh, M., Esmaelian, M. and Rabieh, M. (2015) `The robust linear programming technique for multi-dimensional analysis http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

The robust linear programming technique for multi–dimensional analysis of preferences

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Publishers
ISSN
1756-7017
eISSN
1756-7025
DOI
10.1504/IJIDS.2015.068793
Publisher site
See Article on Publisher Site

Abstract

The linear programming technique for multi-dimensional analysis of preferences (LINMAP) is one of the noted multi-attributes decision making (MADM) techniques and has been implemented in crisp and fuzzy environments. Robust optimisation attempts to obtain a solution which is feasible in all circumstances arising due to the uncertainty of parameters. The purpose of this study is to extend the LINMAP method for addressing robustness in MADM problems. In this methodology, robust optimisation concepts are used to describe robustness in decision information and decision making processes. Each alternative is evaluated based on its weighted distance to a robust positive ideal solution (RPIS). The RPIS and the robust weights of attributes are estimated using a new robust linear programming technique. Finally, Monte Carlo simulation is applied to test the robustness of the solution. A numerical example is provided to illustrate the effectiveness of the methodology. Keywords: linear programming technique for multi-dimensional analysis of preferences; LINMAP; robust optimisation; uncertainty; multi-attributes decision making; MADM. Copyright © 2015 Inderscience Enterprises Ltd. The robust linear programming technique for multi-dimensional analysis Reference to this paper should be made as follows: Mohammadi-Dehcheshmeh, M., Esmaelian, M. and Rabieh, M. (2015) `The robust linear programming technique for multi-dimensional analysis

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2015

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