考虑客户关系管理的绿色闭环供应链网络设计及多目标遗传算法求解

M. Etemad, N. Nezafati, M. Fathi
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引用次数: 0

摘要

背景与目的:温室气体排放和污染物的增加促使组织者和研究人员寻求设计和建立关注环境因素并减少所有部门污染物的网络。因此,本文的主要目标是提出一个考虑客户关系管理的绿色闭环供应链网络的模糊数学规划模型。方法:本研究是在Saba电池公司实施的应用开发研究。在本研究中,提出了一个混合整数线性规划模型来设计一个寻求最小化成本和最小化环境影响的闭环供应链网络。此外,在第三个目标函数的形式中加入了客户关系管理的概念,以最大限度地收集旧产品的数量。结果:考虑到所提模型属于NP-hard范畴,采用多目标遗传算法对模型进行求解,最终确定Pareto解。结果表明,经济目标和环境目标这两个目标是相互矛盾的。也就是说,将每个目标函数移动到期望的目标函数需要将另一个目标函数移动到不希望的目标函数。结论:本研究采用多目标遗传算法对所提出的数学规划模型进行求解,结果表明了设施的位置和容量、生产量、库存量和产品的运输量。
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Green- Closed Loop Supply Chain Network Design by Considering Customer Relationship Management and solving it using Multi-Objective Genetic Algorithm
Background and Objective: Increasing greenhouse gas emissions and pollutants has led organizers and researchers to seek to design and set up networks that focus on environmental factors and reduce pollutants in all sectors. Therefore, the main objective of this paper is to present a fuzzy mathematical programming model for the green closed loop supply chain network, taking into account customer relationship management.Method: This is an applied-development study implemented in Saba Battery Company. In this study, a mixed integer linear programming model is proposed for designing a closed loop supply chain network that seeks to minimize costs and minimize environmental impacts. Also, the concept of customer relationship management in the form of the third objective function has been added to maximize the amount of worn-out product collected to this model.Results: Given that the proposed model belongs to the NP-hard category, a multi-objective genetic algorithm is used to solve the model, and finally, the Pareto's solutions are determined. Based on the results, the two objectives of the economic and environmental objectives are contradictory. That is, moving each one toward the desired one requires movement of the other objective function to the undesirable.Conclusion: In this research, the proposed mathematical programming model has been solved with a multi-objective genetic algorithm, which results indicate the location and capacity of the facility, the amount of production, the amount of inventory and the amount of transportation of the products.
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