Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Foundations of Computing and Decision Sciences Pub Date : 2022-06-01 DOI:10.2478/fcds-2022-0011
Rahmad Syah, M. Nasution, Vladimir Vladimirovich Shol, N. Kireeva, A. Jalil, Tzu-Chia Chen, S. Aravindhan, E. Abood, A. Alkaim
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引用次数: 1

Abstract

Abstract Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization’s priorities, which can be environmental or financial.
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基于双目标优化的某汽车企业绿色供应链运输系统设计
近年来,由于社区对环境问题和环境法规的认识日益提高,公司已经发展到提供更低的价格和更好的质量的产品来留住和吸引客户。经济学也应该关注环境目标。因此,提供一个既能考虑经济目标又能考虑环境目标的供应链模型至关重要。本文以某汽车公司为研究对象,构建了包括供应商、一级仓库、制造工厂、分销商和销售中心在内的绿色直接供应链网络。该模型的目标是使各级转发网络运输的总建设成本、运输成本和二氧化碳排放量最小。本文还采用求解多目标问题的方法之一——权值法绘制了模型,并对模型部分进行了求解。最后,我们讨论了汽车公司应该在多大程度上关注减少二氧化碳,这样管理者就可以根据组织的优先事项(可以是环境的,也可以是财务的)从帕累托边界确定最佳解决方案。
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
期刊最新文献
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