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Order Picking Problem in a Warehouse Hospital Pharmacy

机译:仓库医院药房的订单拣配问题

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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,用于在医院药房的仓库中同时进行路线改进和项目定位,作为订单拣选操作的一部分。在这种精确的背景下,经典的订购单被医疗服务捐赠清单所取代,而医疗捐赠清单却不会随着时间的推移(或不显着)而被修改。这种特殊性允许对订单拣选优化方法进行新的考虑和修改。这项研究的重点是确定仓库中的物料位置以及植根于拣配员到零件的低级策略环境中的拣选员。为了解决所考虑的问题,本文通过混合整数编程模型详细介绍了一种精确的数学求解方法,该模型可以轻松扩展为线性版本。对于实际情况,此类模型可能需要解决计算时间过长的问题。因此,提出了遗传算法和专用的启发式算法,以实现将两种方法结合在一起的混合遗传算法。提供的结果突出了混合方法相对于其他方法在计算时间和解决方案质量方面的贡献。

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