工业闭环供应链网络优化的多目标直觉模糊线性规划模型

S. Kousar, M. Batool, N. Kausar, D. Pamučar, E. Ozbilge, B. Tantay
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引用次数: 0

摘要

在各种工业过程中,对再制造和解决环境问题的迫切需求引起了学术界和实践者对闭环供应链网络(CLSC)的关注。包括社会和经济在内的外部因素不断变化和复杂,对闭环供应链网络的可持续发展产生不利影响。本研究的基本目的是优化CLSC网络的功能。针对上述问题,制定了两个目标函数。第一个目标是使正向和逆向物流的生产成本和装配费用最小化。第二,已作出努力减少与工厂和零售商有关的固定成本。为了实现两个目标函数,采用了三角模糊数和三角直觉模糊数两种方法。两种方法中,三角直觉模糊数实现了上述目标,并有统计学上的优化依据。该方法可以在不影响CLSC网络优化的前提下处理不确定的外部因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-objective Intuitionistic Fuzzy Linear Programming model for optimization of industrial closed-loop supply chain network
The urge to remanufacture and address environmental concerns in various industrial processes has drawn the attention of academics as well as practitioners towards Closed-loop Supply Chain Networks (CLSC). Although everchanging and complex external factors including social and economic ones, adversely impact the sustainable development of closed-loop supply chain networks. The basic aim of the research is to optimize the functioning of CLSC networks. For the above-said, two objective functions are made. The first objective is to minimize the cost of production and assembly expenses of the forward and reverse logistics. Secondly, an endeavour has been made to reduce the fixed costs associated with plants and retailers. For the sake of achieving two objective functions, two methods are employed: triangular fuzzy numbers and triangular intuitionistic fuzzy numbers. Among the two methods, triangular intuitionistic fuzzy numbers achieved the said objectives with greater optimization substantiated by statistics. This method can deal with uncertain external factors without undermining the optimization of the CLSC networks.
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