多通道仓库拣货的最近距离优化与蚁群优化比较

Lukas Bertini, Kai-Uwe Krause, T. Hanne, Rolf Dornberger
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引用次数: 0

摘要

如今,仓库及其背后的IT基础设施确保了所有供应链中客户订单全天的顺利处理。这些订单可以由一个项目到数百个项目组成。仓库的大小和异质性也阻碍了所有订单的最快处理。本研究比较了最近距离优化启发式算法和蚁群优化算法,以找出在几种情况下,根据仓库大小或拣选清单上的物品数量,哪种路径能更快地拣选时间。为此,我们选择了广泛的多通道仓库布局进行研究,假设只有一名工人参与挑选清单上的物品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparison of Nearest Distance Optimization and Ant Colony Optimization for Order Picking in a Multi-Aisle Warehouse
Today, warehouses and the IT infrastructure behind them ensure smooth processing of customer orders throughout the day in all supply chains. These orders can consist of one item up to hundreds of items. The size and heterogeneity of warehouses also impedes the fastest possible processing of all orders. This research compares the nearest distance optimization heuristic and ant colony optimization to find out whether one or the other route leads to faster picking times in several scenarios depending on the warehouse size or the number of items on the picking list. For this purpose, we chose the widespread multi-aisle layout of a warehouse for our study assuming that only one human worker is involved in picking the items on the list.
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