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The research on the inventory routing problem with split pick-ups based on genetic algorithm

机译:基于遗传算法的分担取货的库存路径问题研究

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Modern supply chain management emphasizes coordination of all sectors and improvement of the whole performance. However, most manufacturers focus only on the individual elements of the supply chain (such as inventory, and delivery routes) and fail to consider the interactions in the supply chain. Thus, in this paper, we integrate two principal problems named the inventory control problem and the transportation problem into one problem, and then seek the optimal solution of this combined problem instead of each single problem. A typical supply chain consists of multiple suppliers and one or more assembly plants. In this study, we focus on the multi-period, multi-suppliers, single assembly plant network and set up a mathematics model, and then solve the inventory routing problem with split pick-ups (IRPSP) by genetic algorithm. Finally, we present an example to illustrate the efficiency of method.
机译:现代供应链管理强调各部门的协调和整体绩效的提高。但是,大多数制造商仅关注供应链中的各个要素(例如库存和交货路线),而没有考虑供应链中的相互作用。因此,在本文中,我们将库存控制问题和运输问题这两个主要问题整合为一个问题,然后寻求该组合问题的最佳解决方案,而不是每个问题。典型的供应链由多个供应商和一个或多个组装厂组成。在这项研究中,我们着眼于多周期,多供应商,单装配厂网络并建立一个数学模型,然后通过遗传算法解决带有分离取件(IRPSP)的库存路由问题。最后,我们给出一个例子来说明该方法的有效性。

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