An algorithm for the capacitated vehicle routing problem for picking application in manual warehouses

E. Bottani, G. Casella, Caterina Caccia, R. Montanari
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Abstract

Given that warehouses play a central role in modern supply chains, this study proposes the application of an algorithm for the capacitated vehicle routing problem (CVRP) based on the two-index vehicle flow formulation developed by Baldacci, Hadjiconstantinou, and Mingozzi (2004) for picking purposes in manual warehouses. The study of Theys et al. (2010) is first used to represent the warehouse using a Steiner traveling salesman problem (TSP). Then, a calculation of the picking tour’s length is obtained applying the Manhattan distance. Finally, the algorithm for the CVRP is solved through a cutting plane with the addition of termination criteria related to the capacity of picker. The study analyzes four different warehouse configurations, processing five picking list each. The analysis is carried out exploiting the commercial software MATLAB®, to determine the solution that minimize distance of the order picking tour. The results obtained in MATLAB® show the effectiveness of the chosen algorithm applied to the context of manual order picking.
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人工仓库拣货有能力车辆路径问题的一种算法
鉴于仓库在现代供应链中发挥着核心作用,本研究提出了一种基于Baldacci、Hadjiconstantinou和Mingozzi(2004)开发的双指标车辆流公式的有能力车辆路线问题(CVRP)算法的应用,用于手动仓库的拣选目的。Theys et al.(2010)的研究首先使用Steiner旅行推销员问题(TSP)来表示仓库。然后,利用曼哈顿距离计算出了采摘行程的长度。最后,通过加入与采煤机容量相关的终止准则的切割平面来求解CVRP算法。本研究分析了四种不同的仓库配置,每种配置处理了五种拣货清单。利用商业软件MATLAB®进行分析,以确定最小拣货行程距离的解决方案。在MATLAB®中获得的结果表明,所选算法应用于人工排序的情况下是有效的。
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