任务(项目管理)
单位负荷,单位负荷
托盘
供应链
计算机科学
拣选订单
订单(交换)
单位(环理论)
选择(遗传算法)
运营管理
运筹学
业务
营销
工程类
数学
人工智能
仓库
数学教育
系统工程
财务
作者
Dominic Loske,Tiziana Modica,Matthias Klumpp,Roberto Montemanni
标识
DOI:10.1108/ijlm-04-2023-0150
摘要
Purpose Prior literature has widely established that the design of storage locations impacts order picking task performance. The purpose of this study is to investigate the performance impact of unit loads, e.g. pallets or rolling cages, utilized by pickers to pack products after picking them from storage locations. Design/methodology/approach An empirical analysis of archival data on a manual order picking system for deep-freeze products was performed in cooperation with a German brick-and-mortar retailer. The dataset comprises N = 343,259 storage location visits from 17 order pickers. The analysis was also supported by the development and the results of a batch assignment model that takes unit load selection into account. Findings The analysis reveals that unit load selection affects order picking task performance. Standardized rolling cages can decrease processing time by up to 8.42% compared to standardized isolated rolling boxes used in cold retail supply chains. Potential cost savings originating from optimal batch assignment range from 1.03% to 39.29%, depending on batch characteristics. Originality/value This study contributes to the literature on factors impacting order picking task performance, considering the characteristics of unit loads where products are packed on after they have been picked from the storage locations. In addition, it provides potential task performance improvements in cold retail supply chains.
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