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首页> 外文期刊>International journal of management science and engineering management >A joint inventory reliable capacitated facility location problem using a continuum approximation
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A joint inventory reliable capacitated facility location problem using a continuum approximation

机译：使用连续性近似的联合库存可靠的失能设施位置问题

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摘要

This paper considers a continuum approximation to deal with a joint inventory reliable capacitated facility location problem within a two-echelon supply chain structure, whereas the majority of related studies assume facilities with infinite capacity and neglect inventory cost. The scope of the supply chain is restricted to distribution-centers (DCs) and customers, whereas they are spatially distributed over the market area. As DCs are vulnerable to permanent failure, different assignment levels are regarded for customers. The resulting model formulation partitions the market area into the different districts of DCs and consequently obtains the total required number of DCs. It also allocates a portion of the districts to the assignment levels. Since the model formulation is a nonlinear programming problem with box-constraint variables, we employ a trust region algorithm (TRA) as the solution procedure. A genetic algorithm (GA) is used as a benchmark for the proposed solution procedure. The computational results demonstrate the superiority of the TRA in terms of cost and time savings. Numerically, TRA improves the objective function by about 10% compared with the GA. The sensitivity analysis also indicates the enlargement of the number of districts as a result of increasing the vulnerability of DCs. Finally, the amount of enlargement is affected by a trade-off between transportation, inventory, and penalty costs on the one hand and fixed costs on the other.
机译：本文考虑了连续性近似来处理两级供应链结构中联合库存可靠的带功能设施的选址问题，而大多数相关研究都假设设施的容量无限且忽略了库存成本。供应链的范围仅限于配送中心（DC）和客户，而它们在空间上分布在整个市场区域。由于DC容易遭受永久性故障，因此为客户考虑了不同的分配级别。生成的模型公式将市场区域划分为DC的不同区域，从而获得所需的DC总数。它还将部分分区分配给分配级别。由于模型制定是具有约束变量的非线性规划问题，因此我们采用信任域算法（TRA）作为求解过程。遗传算法（GA）用作提出的解决方案的基准。计算结果证明了TRA在成本和时间节省方面的优势。在数值上，与GA相比，TRA将目标函数提高了约10％。敏感性分析还表明，由于DC的脆弱性增加，导致地区数量的增加。最后，扩大量一方面受到运输，库存和罚款成本之间的权衡，另一方面受到固定成本的影响。

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