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

机译:设计多产品多期限两级供应链网络,以通过差异演化使牛鞭效应最小化

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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:供应链网络由分布在不同地理位置的设施组成。通过确定订单数量和连接设施的链接的分布,可以优化此网络结构以使总成本或总库存最小化。但是,牛鞭效应(即,订单波动的放大)是供应链的重要绩效指标,因为随着供应链下游(例如分销商)订单差异的增加,上游(例如制造商)的需求差异放大并导致供应链效率低下。在这项研究中,我们优化了多产品多期限两级供应链网络的供应链网络结构,以最大程度地减少牛鞭效应。由于目标函数的非线性结构,即牛鞭效应,本文提出了一种采用变量邻域搜索(VNS)和约束处理方法来优化供应链网络结构的差分进化(DE)算法。该算法在随机生成的测试实例上进行了测试,并证明了其有效性。

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