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Order Picking Problem in a Warehouse Hospital Pharmacy

机译:仓库医院药房的订单挑选问题

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This paper presents an optimization method for simultaneously routing improvement and items location as part of order picking operation in a warehouse of a hospital pharmacy. In this precise context, the classical order forms are replaced by medical services endowment lists which are not modified over time (or not significantly). This particularity allows new considerations and modifications of the order picking optimization methods. This study focuses on the items location determination in the warehouse and the pickers rooting in a picker-to-part low level policy context. In order to solve the considered problem, the paper details an exact mathematical solving method through a mix integer programing model which can easily be extended to a linear version. For real case, this class of model may need prohibitive computation times to be solved. Consequently, a genetic algorithm and a dedicated heuristic are presented in order to implement a hybrid genetic algorithm which is the combination of both methods. Results are provided to highlight the contribution of the hybrid method compared to the others in terms of computation times and solutions quality.
机译:本文提出了一种优化方法,用于同时路由改善和物品位置,作为医院药房仓库中订单采摘操作的一部分。在这种精确的上下文中,经典订单表单由医疗服务禀赋列表替换,这些列表不会随时间(或不显着)修改。这种特殊性允许新的考虑和修改订单拣选优化方法。本研究重点介绍仓库中的物品位置确定,并在拾取器到部分低级策略上下文中扎根。为了解决所考虑的问题,纸张通过混合整数编程模型详细说明了一个精确的数学求解方法,该模型可以很容易地扩展到线性版本。对于真实的情况,这类模型可能需要解决禁止的计算时间。因此,提出了一种遗传算法和专用启发式,以实现一种混合遗传算法,该遗传算法是两种方法的组合。提供了结果,以突出混合方法与其他在计算时间和解决方案质量方面的贡献。

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