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Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm AbstractEnvironmental threats of coal usage in the electricity production combined with the consumption of renewable and non-renewable resources had led to worldwide energy challenges. The cost of coal mining and economical and environmentally sustainable usage of mined coal could be optimized by efficient management of coal supply chain. This paper provides a mathematical model for improving coal supply chain sustainability including the cost of exergy destruction (entropy). In the proposed method, exergy analysis is used to formulate the model considering not only economic costs but also destructed exergy cost, while genetic algorithm is applied to efficiently solve the proposed model. In order to validate the proposed methodology, some numerical examples of coal supply chains are presented and discussed to show the usability of the proposed exergetic coal supply chain model and claim its benefits over the existing models. According to the results, the proposed method provides 17.6% saving in the consumed exergy by accepting 2.7% more economic costs. The presented model can be used to improve the sustainability of coal supply chain for either designing new projects or upgrading existing processes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Systems in Production Engineering de Gruyter

Sustainable Coal Supply Chain Management Using Exergy Analysis and Genetic Algorithm

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References (44)

Publisher
de Gruyter
Copyright
© 2021 Reihaneh Naderi et al., published by Sciendo
eISSN
2450-5781
DOI
10.2478/mspe-2021-0006
Publisher site
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Abstract

AbstractEnvironmental threats of coal usage in the electricity production combined with the consumption of renewable and non-renewable resources had led to worldwide energy challenges. The cost of coal mining and economical and environmentally sustainable usage of mined coal could be optimized by efficient management of coal supply chain. This paper provides a mathematical model for improving coal supply chain sustainability including the cost of exergy destruction (entropy). In the proposed method, exergy analysis is used to formulate the model considering not only economic costs but also destructed exergy cost, while genetic algorithm is applied to efficiently solve the proposed model. In order to validate the proposed methodology, some numerical examples of coal supply chains are presented and discussed to show the usability of the proposed exergetic coal supply chain model and claim its benefits over the existing models. According to the results, the proposed method provides 17.6% saving in the consumed exergy by accepting 2.7% more economic costs. The presented model can be used to improve the sustainability of coal supply chain for either designing new projects or upgrading existing processes.

Journal

Management Systems in Production Engineering – de Gruyter

Published: Mar 1, 2021

Keywords: coal supply chain; exergy; genetic algorithm; sustainability

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