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Design of multi-product multi-period two-echelon supply chain network to minimize bullwhip effect through differential evolution

机译:多产品多时期双梯电源链网络设计,以通过差分演变最大限度地减少牛鞭效应

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摘要

A supply chain network consists of facilities located in dispersed geographical locations. This network structure can be optimized to minimize total cost or total inventory by deciding the order quantities and distribution of links connecting the facilities. However, bullwhip effect (i.e., amplification of order fluctuations) is an important performance metric for supply chains because as the order variance increases in the downstream of the supply chain (e.g., distributors), the demand variance in the upstream (e.g., manufacturer) amplifies and causes inefficiencies in the supply chain. In this study, we optimize supply chain network structure for multi-product multi-period two-echelon supply chain networks to minimize bullwhip. Due to nonlinear structure of the objective function, i.e., bullwhip effect, this paper proposes a differential evolution (DE) algorithms employing variable neighborhood search (VNS) and constraint handling methods to optimize supply chain network structure. The proposed algorithm is tested over randomly generated test instances and its effectiveness is demonstrated.
机译:供应链网络由位于分散地理位置的设施组成。可以优化该网络结构以通过决定连接设施的链路的顺序和分布来最小化总成本或总库存。但是,牛鞭效应(即,订单波动的放大)是供应链的重要性能度量,因为随着所订单方差在供应链(例如,分销商)的下游增加,上游的需求方差(例如,制造商)放大并导致供应链的低效率。在本研究中,我们优化了用于多产品多时期双梯电源链网络的供应链网络结构,以最大限度地减少牛鞭。由于目标函数的非线性结构,即牛鞭效应,本文提出了采用可变邻域搜索(VNS)和约束处理方法的差分演进(DE)算法来优化供应链网络结构。在随机生成的测试实例上测试了所提出的算法,并且证明其有效性。

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