{"title":"A real‐life study on the value of integrated optimization in order picking operations under dynamic order arrivals","authors":"Ruben D'Haen, Katrien Ramaekers, Stef Moons, Kris Braekers","doi":"10.1002/net.22237","DOIUrl":null,"url":null,"abstract":"Optimizing the order picking operations is indispensable for warehouses that promise a high customer service level. While many areas for improvement have been identified and studied in the literature, a large gap remains between academia and practice. To help with closing this gap, we perform a case‐study in collaboration with a spare‐parts warehouse in Belgium. In this study, we optimize the order picking operations of the company, using the actual warehouse layout and real order data. A state‐of‐the‐art online integrated order batching, picker routing and batch scheduling algorithm is adapted to consider multiple real‐life constraints. More specifically, the dynamic arrival of new orders is considered, and a capacity constraint on the sorting installation should be respected. Furthermore, a new waiting strategy is studied in which order pickers can temporarily postpone certain orders, as combining them with possible future order arrivals may allow for more efficient overall picking performance. Finally, the performance of the current operating policy is compared with that of both a seed batching heuristic and our metaheuristic algorithm by use of an ANOVA analysis. The results indicate that the number of order pickers can be reduced by 12.5% if the new optimization algorithm is used, accompanied by an improvement in the offered customer service level.","PeriodicalId":54734,"journal":{"name":"Networks","volume":"29 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Networks","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/net.22237","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
Optimizing the order picking operations is indispensable for warehouses that promise a high customer service level. While many areas for improvement have been identified and studied in the literature, a large gap remains between academia and practice. To help with closing this gap, we perform a case‐study in collaboration with a spare‐parts warehouse in Belgium. In this study, we optimize the order picking operations of the company, using the actual warehouse layout and real order data. A state‐of‐the‐art online integrated order batching, picker routing and batch scheduling algorithm is adapted to consider multiple real‐life constraints. More specifically, the dynamic arrival of new orders is considered, and a capacity constraint on the sorting installation should be respected. Furthermore, a new waiting strategy is studied in which order pickers can temporarily postpone certain orders, as combining them with possible future order arrivals may allow for more efficient overall picking performance. Finally, the performance of the current operating policy is compared with that of both a seed batching heuristic and our metaheuristic algorithm by use of an ANOVA analysis. The results indicate that the number of order pickers can be reduced by 12.5% if the new optimization algorithm is used, accompanied by an improvement in the offered customer service level.
期刊介绍：
Network problems are pervasive in our modern technological society, as witnessed by our reliance on physical networks that provide power, communication, and transportation. As well, a number of processes can be modeled using logical networks, as in the scheduling of interdependent tasks, the dating of archaeological artifacts, or the compilation of subroutines comprising a large computer program. Networks provide a common framework for posing and studying problems that often have wider applicability than their originating context.
The goal of this journal is to provide a central forum for the distribution of timely information about network problems, their design and mathematical analysis, as well as efficient algorithms for carrying out optimization on networks. The nonstandard modeling of diverse processes using networks and network concepts is also of interest. Consequently, the disciplines that are useful in studying networks are varied, including applied mathematics, operations research, computer science, discrete mathematics, and economics.
Networks publishes material on the analytic modeling of problems using networks, the mathematical analysis of network problems, the design of computationally efficient network algorithms, and innovative case studies of successful network applications. We do not typically publish works that fall in the realm of pure graph theory (without significant algorithmic and modeling contributions) or papers that deal with engineering aspects of network design. Since the audience for this journal is then necessarily broad, articles that impact multiple application areas or that creatively use new or existing methodologies are especially appropriate. We seek to publish original, well-written research papers that make a substantive contribution to the knowledge base. In addition, tutorial and survey articles are welcomed. All manuscripts are carefully refereed.
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