Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm

Success in supply chain implementation depends on the way of dealing with market changes and customer needs. Agility is a concept that has been introduced in recent years to improve the supply chain. On the other hand, paying attention to environmental problems is another issue, and chains are tryin...

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Autores principales: Liu Kai, Ramina Malekalipour Kordestanizadeh
Formato: article
Lenguaje:EN
Publicado: Hindawi Limited 2021
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Acceso en línea:https://doaj.org/article/e7ce7d93b9bb478893fb4baa80a5fe90
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spelling oai:doaj.org-article:e7ce7d93b9bb478893fb4baa80a5fe902021-11-15T01:20:04ZDesigning an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm1563-514710.1155/2021/3811417https://doaj.org/article/e7ce7d93b9bb478893fb4baa80a5fe902021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3811417https://doaj.org/toc/1563-5147Success in supply chain implementation depends on the way of dealing with market changes and customer needs. Agility is a concept that has been introduced in recent years to improve the supply chain. On the other hand, paying attention to environmental problems is another issue, and chains are trying to increase their popularity by focusing on this issue. Considering the importance of this issue, designing a multiobjective closed-loop supply chain network has been discussed in this research. The main contribution of this research is the integration of green and agility concepts in supply chain design. In this regard, a mathematical model is presented with economic, environmental, and agility objectives. First, the mathematical model is solved using the Epsilon constraint method, and then, the multiobjective weed algorithm is proposed to solve the model. The results of comparisons between the two methods show that the multiobjective weed algorithm has performed well in terms of various metrics of NPS, SNS, and Max Spread. In terms of the solving time, the average solving time of this algorithm was about 0.1% of the solving time of the Epsilon constraint method. Moreover, all cases show the superiority of the multiobjective weed algorithm over the Epsilon constraint method in solving the proposed mathematical model.Liu KaiRamina Malekalipour KordestanizadehHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution DOAJ
collection DOAJ
language EN
topic Engineering (General). Civil engineering (General)
TA1-2040
Mathematics
QA1-939
spellingShingle Engineering (General). Civil engineering (General)
TA1-2040
Mathematics
QA1-939
Liu Kai
Ramina Malekalipour Kordestanizadeh
Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
description Success in supply chain implementation depends on the way of dealing with market changes and customer needs. Agility is a concept that has been introduced in recent years to improve the supply chain. On the other hand, paying attention to environmental problems is another issue, and chains are trying to increase their popularity by focusing on this issue. Considering the importance of this issue, designing a multiobjective closed-loop supply chain network has been discussed in this research. The main contribution of this research is the integration of green and agility concepts in supply chain design. In this regard, a mathematical model is presented with economic, environmental, and agility objectives. First, the mathematical model is solved using the Epsilon constraint method, and then, the multiobjective weed algorithm is proposed to solve the model. The results of comparisons between the two methods show that the multiobjective weed algorithm has performed well in terms of various metrics of NPS, SNS, and Max Spread. In terms of the solving time, the average solving time of this algorithm was about 0.1% of the solving time of the Epsilon constraint method. Moreover, all cases show the superiority of the multiobjective weed algorithm over the Epsilon constraint method in solving the proposed mathematical model.
format article
author Liu Kai
Ramina Malekalipour Kordestanizadeh
author_facet Liu Kai
Ramina Malekalipour Kordestanizadeh
author_sort Liu Kai
title Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
title_short Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
title_full Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
title_fullStr Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
title_full_unstemmed Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm
title_sort designing an agile closed-loop supply chain with environmental aspects using a novel multiobjective metaheuristic algorithm
publisher Hindawi Limited
publishDate 2021
url https://doaj.org/article/e7ce7d93b9bb478893fb4baa80a5fe90
work_keys_str_mv AT liukai designinganagileclosedloopsupplychainwithenvironmentalaspectsusinganovelmultiobjectivemetaheuristicalgorithm
AT raminamalekalipourkordestanizadeh designinganagileclosedloopsupplychainwithenvironmentalaspectsusinganovelmultiobjectivemetaheuristicalgorithm
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