Robust supplier selection in a closed loop supply chain using a hybrid approach based on design of experiments and simulation

A. Salmasnia, S. Cheraghi, A. Ghorbanian, H. Mokhtari
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引用次数: 4

Abstract

Supplier evaluation and selection is a vital problem in supply chain management of which the two most important factors are procurement cost and products quality level. Researchers have investigated many aspects of this problem so far. These factors, as delivery time and customer behaviour against product quality, are uncertain. Nevertheless, for the purpose of simple application, they are usually considered deterministic. To have more accurate modelling of the real world, it is necessary to consider these uncertain factors in models. Making sure that chain profit and product quality satisfy the decision maker, this paper develops a robust approach based on design of experiments and simulation for selection of suppliers in a closed loop supply chain, product quality. By implementing signal-to-noise ratio, variances of cost and product quality, as secondary objectives in optimisation process, are minimised to reduce the effect of noise factors on the objective functions under consideration.
基于实验设计和仿真的闭环供应链鲁棒供应商选择方法
供应商评价与选择是供应链管理中的一个重要问题,其中最重要的两个因素是采购成本和产品质量水平。到目前为止,研究人员已经研究了这个问题的许多方面。这些因素,如交货时间和顾客行为对产品质量的影响,都是不确定的。然而,为了简单的应用程序,它们通常被认为是确定性的。为了对现实世界进行更精确的建模,有必要在模型中考虑这些不确定因素。在保证供应链利润和产品质量满足决策者要求的前提下,提出了一种基于实验设计和仿真的闭环供应链供应商选择、产品质量的鲁棒方法。通过实现信噪比,成本和产品质量的差异作为优化过程中的次要目标被最小化,以减少噪声因素对所考虑的目标函数的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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