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A bi-objective model for a multi-echelon supply chain design considering efficiency and customer satisfaction: a case study in plastic parts industry

机译:考虑效率和顾客满意度的多梯队供应链设计的双目标模型 - 以塑料零件行业为例

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摘要

One of the fundamental challenges of today's manufacturing systems is the contradiction between cost efficiency and customer satisfaction. Finding a good balance between good customer satisfaction and supply chain efficiency is a critical problem in the supply chain management. To achieve this goal, a bi-objective mathematical model is suggested in this paper to maximize the efficiency of network and also customer satisfaction. This multi-period and multi-product supply chain network design model consists of suppliers, factories, distribution centers (DCs), and customers. The proposed bi-objective mixed-integer non-linear programming (MINLP) model is a member of the NP-hard class of optimization problems. Hence, two well-known multi-objective metaheuristic algorithms namely, Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Non-dominated Ranked Genetic Algorithm (NRGA) are employed to solve the proposed model. The author uses Taguchi method for tuning the parameters of algorithms in order to achieve better performances. Moreover, a case study in the plastic industry is performed to collect data from the north region of Iran. Some well-known multi-objective metrics such as analysis of variance (ANOVA) is used to measure the performance of the proposed framework. Finally, results demonstrate the efficiency of the proposed framework.
机译:今天的制造系统的基本挑战之一是成本效率与客户满意度之间的矛盾。在良好的客户满意度和供应链效率之间找到良好的平衡是供应链管理中的一个关键问题。为实现这一目标,本文提出了一种双目标数学模型,以最大限度地提高网络的效率以及客户满意度。该多时期和多产品供应链网络设计模型包括供应商,工厂,分销中心(DCS)和客户组成。所提出的双目标混合整数非线性编程(MINLP)模型是NP-Hard类优化问题的成员。因此,使用了两个众所周知的多目标成帧算法II(NSGA-II)和非主导的排名遗传算法(NRGA)来解决所提出的模型。作者使用Taguchi方法来调整算法的参数,以便实现更好的性能。此外,在塑料行业进行案例研究以收集来自伊朗北部地区的数据。一些众所周知的多目标度量等多目标度量,例如方差分析(ANOVA)用于测量所提出的框架的性能。最后,结果证明了所提出的框架的效率。

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