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OPTIMISATION OF STOCK KEEPING UNIT PLACEMENT IN A RETAIL DISTRIBUTION CENTRE

机译:零售配送中心的库存保持单元位置的优化

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The retail problem of slotting refers to the assignment of stock keeping units (SKUs) to the available storage locations in a distribution centre (DC). Generally, the expected total distance travelled by stock pickers during an order consolidation and the resulting level of congestion experienced within aisle racking are common considerations when making these assignments. These criteria give rise to a bi-objective optimisation model with the aim of identifying multiple stock setups that achieve acceptable trade-offs between minimising the criteria on expectation. A mathematical framework is established in this paper, based on these two criteria, for evaluating the effectiveness of a given stock setup. In the framework, a stock picker’s movement between various storage locations is modelled as a Markov chain in order to quantify his or her expected travel distance, while a closed queuing network model is used to devise a suitable measure of congestion. This optimisation model framework forms the basis of a flexible decision support system (DSS) for the purpose of discovering high-quality stock assignment trade-off solutions for inventory managers. The DSS is applied to a special case study involving data from a real DC, and the desirability of the recommended stock configurations is compared with that currently implemented within the DC.
机译:进货的零售问题是指将库存单位(SKU)分配给配送中心(DC)中的可用存储位置。通常,在进行这些分配时,通常会考虑选货员在订单合并过程中预期的总距离以及过道货架中所导致的拥堵程度。这些标准产生了一个双目标优化模型,其目的是确定在使期望标准最小化之间实现可接受折衷的多个库存设置。本文基于这两个标准建立了数学框架,用于评估给定库存设置的有效性。在该框架中,选货员在各个存储位置之间的移动被建模为马尔可夫链,以量化其预期的行进距离,同时使用封闭排队网络模型来设计适当的拥堵度量。该优化模型框架构成了灵活的决策支持系统(DSS)的基础,旨在为库存管理者发现高质量的库存分配权衡解决方案。 DSS应用于涉及来自实际DC的数据的特殊案例研究,并将推荐的库存配置的可取性与DC中当前实施的需求进行了比较。

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