Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach
In this paper, we propose a solution to the sustainable closed-loop supply chain (SCLSC) design problem. Three factors (economic, environmental, and social) are considered for the problem and the three following requirements are addressed while satisfying associated constraint conditions: (i) minimi...
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MDPI AG
2020-01-01
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Online Access: | https://www.mdpi.com/2227-7390/8/1/84 |
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author | YoungSu Yun Anudari Chuluunsukh Mitsuo Gen |
author_facet | YoungSu Yun Anudari Chuluunsukh Mitsuo Gen |
author_sort | YoungSu Yun |
collection | DOAJ |
description | In this paper, we propose a solution to the sustainable closed-loop supply chain (SCLSC) design problem. Three factors (economic, environmental, and social) are considered for the problem and the three following requirements are addressed while satisfying associated constraint conditions: (i) minimizing the total cost; (ii) minimizing the total amount of CO<sub>2</sub> emission during production and transportation of products; (iii) maximizing the social influence. Further, to ensure the efficient distribution of products through the SCLSC network, three types of distribution channels (normal delivery, direct delivery, and direct shipment) are considered, enabling a reformulation of the problem as a multi-objective optimization problem that can be solved using Pareto optimal solutions. A mathematical formulation is proposed for the problem, and it is solved using a hybrid genetic algorithm (pro-HGA) approach. The performance of the pro-HGA approach is compared with those of other conventional approaches at varying scales, and the performances of the SCLSC design problems with and without three types of distribution channels are also compared. Finally, we prove that the pro-HGA approach outperforms its competitors, and that the SCLSC design problem with three types of distribution channels is more efficient than that with a single distribution channel. |
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spelling | doaj.art-f8934d98018a4bb98f698b109abe723f2022-12-22T03:00:52ZengMDPI AGMathematics2227-73902020-01-01818410.3390/math8010084math8010084Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm ApproachYoungSu Yun0Anudari Chuluunsukh1Mitsuo Gen2Department of Business Administration, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, KoreaDepartment of Business Administration, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, KoreaFuzzy Logic Systems Institute, Tokyo University of Science, 1-3 Kagurazaka Shinjiku-ku, Tokyo 162-8601, JapanIn this paper, we propose a solution to the sustainable closed-loop supply chain (SCLSC) design problem. Three factors (economic, environmental, and social) are considered for the problem and the three following requirements are addressed while satisfying associated constraint conditions: (i) minimizing the total cost; (ii) minimizing the total amount of CO<sub>2</sub> emission during production and transportation of products; (iii) maximizing the social influence. Further, to ensure the efficient distribution of products through the SCLSC network, three types of distribution channels (normal delivery, direct delivery, and direct shipment) are considered, enabling a reformulation of the problem as a multi-objective optimization problem that can be solved using Pareto optimal solutions. A mathematical formulation is proposed for the problem, and it is solved using a hybrid genetic algorithm (pro-HGA) approach. The performance of the pro-HGA approach is compared with those of other conventional approaches at varying scales, and the performances of the SCLSC design problems with and without three types of distribution channels are also compared. Finally, we prove that the pro-HGA approach outperforms its competitors, and that the SCLSC design problem with three types of distribution channels is more efficient than that with a single distribution channel.https://www.mdpi.com/2227-7390/8/1/84sustainable closed-loop supply chainmulti-objective optimizationpareto optimal solutionhybrid genetic algorithmeconomicenvironmentalsocial factors |
spellingShingle | YoungSu Yun Anudari Chuluunsukh Mitsuo Gen Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach Mathematics sustainable closed-loop supply chain multi-objective optimization pareto optimal solution hybrid genetic algorithm economic environmental social factors |
title | Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach |
title_full | Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach |
title_fullStr | Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach |
title_full_unstemmed | Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach |
title_short | Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach |
title_sort | sustainable closed loop supply chain design problem a hybrid genetic algorithm approach |
topic | sustainable closed-loop supply chain multi-objective optimization pareto optimal solution hybrid genetic algorithm economic environmental social factors |
url | https://www.mdpi.com/2227-7390/8/1/84 |
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