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Two-warehouse production inventory model for a deteriorating item with time-varying demand and shortages: a genetic algorithm with varying population size approach

机译:具有时变需求和短缺的变质物品的两仓库生产库存模型:具有可变人口规模方法的遗传算法

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A production-inventory model for a deteriorating item with time-varying demand and fully backlogged shortages is developed for a two warehouse system. For display and storage of inventory, management hires one warehouse of finite capacity at the market place, called own warehouse abbreviated as OW and another warehouse with large capacity as it may be required at a distance place from the market, called rented warehouse abbreviated as RW. Though the time of transporting items from RW to OW is ignored the transportation cost for transporting items is taken to be dependent on the transported amount. Here the objective is to minimize the total cost for a finite planning horizon. A genetic algorithm (GA) is designed to determine the optimum number of production cycles and the cycle times within a finite planning horizon. In this GA a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. Performance of this GA with respect to some other GAs is compared. Two particular cases (ⅰ) with non-deteriorating items and (ⅱ) without shortages are also investigated. Finally, to illustrate the model and to show the effectiveness of the proposed approach, a numerical example is provided. With respect to the demand parameters, a sensitivity analysis is performed and presented. In this paper, we have pointed out that the expression of Lee and Hsu (2009) can be obtained as a particular case.
机译:针对两仓库系统,开发了具有时变需求且完全积压的短缺的变质产品的生产库存模型。为了显示和存储库存,管理人员在市场上租用了一个容量有限的仓库,称为自己的仓库,简称为OW,而在距离市场较远的地方可能需要另一个大容量的仓库,称为租赁仓库,简称为RW 。虽然忽略了从RW到OW的运输时间,但运输物品的运输成本被视运输量而定。此处的目标是使有限的计划范围内的总成本最小化。设计遗传算法(GA)来确定有限计划范围内的最佳生产周期数和周期时间。在此GA中,下一代的父母群体中包括子代更好的子代,并且该子集的大小是其父集大小的百分比。比较了该GA与其他某些GA的效果。还研究了两种特殊情况(ⅰ)物品没有变质,(ⅱ)没有短缺。最后,为了说明该模型并显示所提出方法的有效性,提供了一个数值示例。关于需求参数,执行并给出敏感性分析。在本文中,我们指出了Lee和Hsu(2009)的表达式可以作为一个特定案例获得。

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