Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse
Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse
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DOI：
10.1080/00207540500142894
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发表时间：
2005-09
影响因子：
9.2
通讯作者：
T. Le-Duc *;René de Koster
中科院分区：
文献类型：
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作者：
T. Le-Duc *;René de Koster
订单拣选被认为是仓储中最关键的操作。物流的最新趋势需要更快但更可靠的订单拣选系统。订单拣选流程的效率很大程度上取决于所使用的存储策略，即产品在仓库中的位置。在本文中，我们讨论最流行的存储策略，即基于类（或 ABC）的存储策略。特别是，我们研究了确定手动操作仓库每个通道中类别的最佳存储边界（区域）的问题。我们首先提出了一个概率模型，使我们能够估计采摘之旅的平均旅行距离。我们发现模拟结果与模型结果之间的差异很小。使用平均行驶距离作为目标函数，我们提出了存储区优化问题的数学公式。然而，确切的方法只能处理小型仓库实例。为了规避这个障碍，我们提出了一个针对该问题的启发式方法。我们进行的数值示例表明启发式方法在所有情况下都表现良好。
Order picking has been considered as the most critical operation in warehousing. Recent trends in logistics demand faster but more reliable order picking systems. The efficiency of an order picking process greatly depends on the storage policy used, i.e. where products are located within the warehouse. In this paper, we deal with the most popular storage policy that is class-based (or ABC) storage strategy. Particularly, we investigate the problem of determining the optimal storage boundaries (zones) of classes in each aisle for manually operated warehouses. We first propose a probabilistic model that enables us to estimate the average travel distance of a picking tour. We found that the differences between results obtained from simulation and the model were slight. Using the average travel distance as the objective function, we present a mathematical formulation for the storage zone optimization problem. However, the exact approach can handle only small size warehouse instances. To circumvent this obstacle, we propose a heuristic for the problem. Numerical examples we conducted show that the heuristic performs very well in all the cases.