Measuring the impact of (s, S) ordering policy on the bullwhip effect by means of simulation optimization

Mouna Derbel, H. Chabchoub, Wafik Hachicha, F. Masmoudi
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引用次数: 2

Abstract

An important supply chain research problem is the bullwhip effect (BE), which its presence makes supply chain planning difficult. In fact, demand fluctuations increase as one move up the supply chain from retailer to manufacturer. In this paper, a single-stage supply chain for a single-item inventory system is considered. The aim is about how identify the critical parameters that affect BE phenomenon when the retailer employ a (s, S) policy. To investigate and measure this impact, a simulation model is developed using Arena 10 software. A simulation-optimization based-approach is adopted, which combines metamodel through the factorial design experiments and the desirability function approach. Our findings suggest that when we want to reduce the BE, this doesn't mean directly reduce costs. The BE must be introduced in the supply chain management such a constraint not such an objective function (BE must be lower to 1 to have not a bullwhip effect), and the effect of S is always more significant than the effect of s, and it is valid for all studied situations. Otherwise, in a (s, S) policy, the choice of S is more determinant that s, to reduce costs in the supply chains as well BE.
采用仿真优化的方法测量(s, s)排序策略对牛鞭效应的影响
牛鞭效应是供应链研究中的一个重要问题,它的存在给供应链规划带来了困难。事实上,从零售商到制造商,需求波动会随着供应链的上升而增加。本文考虑单品库存系统下的单阶段供应链问题。目的是关于当零售商采用(s, s)策略时,如何识别影响BE现象的关键参数。为了调查和测量这种影响,使用Arena 10软件开发了一个仿真模型。采用基于仿真优化的方法,将析因设计实验的元模型与期望函数方法相结合。我们的研究结果表明,当我们想要降低经济效益时,这并不意味着直接降低成本。在供应链管理中引入BE必须是这样一个约束,而不是这样一个目标函数(BE必须小于1才不会产生牛鞭效应),并且S的效果总是比S的效果更显著,并且对所有研究的情况都有效。否则,在(s, s)策略中,选择s比选择s更具决定性,以降低供应链中的成本。
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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