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A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm

机译:短缺情况下的模糊供应商管理的多项目经济订单数量模型库存:蚁群算法

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摘要

In this study, a multi-item economic order quantity model with shortage under vendor managed inventory policy in a single vendor single buyer supply chain is developed. This model explicitly includes warehouse capacity and delivery constraints, bounds order quantity, and limits the number of pallets. Not only the demands are considered imprecise, but also resources such as available storage and total order quantity of all items can be vaguely defined in different ways. An ant colony optimization is employed to find a near-optimum solution of the fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Since no benchmark is available in the literature, a genetic algorithm and a differential evolution are developed as well to validate the result obtained. Furthermore, the applicability of the proposed methodology along with a sensitivity analysis on its parameter is demonstrated using five numerical examples containing different numbers of items.
机译:在这项研究中,开发了一个多项目经济订单数量模型,该模型在单个卖方单买方供应链中由卖方管理的库存策略下短缺。该模型明确包括仓库容量和交付约束,限制订单数量以及限制托盘数量。不仅认为需求不准确,而且可以用不同的方式模糊地定义所有项目的资源(例如可用存储量和所有项目的总订购量)。为了最小化供应链的总成本,采用蚁群优化来找到模糊非线性整数规划问题的近似最优解。由于文献中没有基准可用,因此也开发了遗传算法和差分进化来验证获得的结果。此外,使用五个包含不同数量项目的数值示例,证明了所提出方法的适用性及其参数的敏感性分析。

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