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Minimizing Travel Distance During Warehouse Order Picking Considering Congestion Effect

机译：考虑拥挤效应的最小化仓库订单拣选中的行进距离

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摘要

Order picking is considered as one of the most costly and time-consuming processes in a manual picker-to-order system. The process is as follows: pickers receive customer orders and then start collecting the order items by picking these items from their storage locations. Finding the most efficient route to visit all items locations is the main goal of optimizing order picking routing path. Because each warehouse runs its operations with multiple pickers and the pickers may work in the same zone to pick items on customer orders, congestion may occur during the picking time. This can affect the order picking finishing time. The optimization solution obtained without considering the order picking congestion might not provide the most efficient route.;Among all warehouse operations, order picking accounts for almost 55%-65% of the total cost. Around 50%-55% of the order picking time is for traveling between picking locations. Most of the studies focus on the single picker-to-order systems, where the effect of the congestion does not exist. However, in reality, multiple picker systems were used and thus congestion does have a significant impact on order picking. This represents an important gap in the literature, where there is no mathematical formulation for the congestion in the literature.;This research focuses on the congested order-picking problem, and solve for the best picking route while considering the effect of different factors inside the warehouse. Literature is investigated to survey the studies that considered the congestion effect in multiple picker systems and to review the models used to represent this problem.;Three models (represents order picking without congestion consideration, with picking face congestion, and with picking and aisle congestion) were defined. In addition, three levels of congestion were defined. The Model I was solved using Tabu Search, Genetic Algorithm, and Hybrid Algorithm. Algorithms validated by comparing with CPLEX solution. Then, the most efficient algorithm was used to solve both Model II and Model III. A sensitivity analysis was done to explain the effect of different combinations (order pickers number, the number of items to be picked, and the width of the aisle) on the level of congestion.
机译：订单拣选被认为是手动拣货到订单系统中最昂贵，最耗时的过程之一。该过程如下：拣配者接收客户订单，然后通过从其存储地点拣选这些项目开始收集订单项目。寻找最有效的路线来访问所有物品的位置是优化订单拣选路线的主要目标。因为每个仓库都由多个拣货员运行其操作，并且拣货员可能在同一区域内工作以拣选客户订单中的物品，所以在拣选时间内可能会出现拥堵。这可能会影响订单拣选的完成时间。不考虑订单拣选拥堵而获得的优化解决方案可能无法提供最有效的途径。在所有仓库操作中，订单拣选几乎占总成本的55％-65％。订单拣选时间的大约50％-55％用于在拣选地点之间旅行。大多数研究集中在不存在拥塞效应的单一按订单订购系统中。但是，实际上，使用了多个拣选系统，因此拥堵确实对订单拣选产生重大影响。这代表了文献中的一个重要空白，在文献中没有数学公式来表示拥塞。仓库。对文献进行调查以调查考虑了多个拣选器系统中拥塞效应的研究，并回顾用于表示此问题的模型。三种模型（代表不考虑拥塞的订单拣选，拣选工作面拥挤以及拣选和过道拥挤）被定义。另外，定义了三个拥塞级别。使用禁忌搜索，遗传算法和混合算法解决了模型I。通过与CPLEX解决方案进行比较来验证算法。然后，使用最有效的算法来求解模型II和模型III。进行了敏感性分析，以解释不同组合（订单分拣机数量，要分拣的物品数量以及过道的宽度）对拥挤程度的影响。

著录项

  • 作者

    Bataineh, Mohammad.;

  • 作者单位

    State University of New York at Binghamton.;

  • 授予单位 State University of New York at Binghamton.;
  • 学科 Operations research.;Industrial engineering.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 110 p.
  • 总页数 110
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 水产、渔业;
  • 关键词

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