{"title":"An improved crossover particle swarm optimization algorithm for automatic order sorting in distribution center","authors":"Yuze Xu, Linxuan Zhang, Hui Li, M. Ge, Wanyi He","doi":"10.1109/ICMA54519.2022.9856225","DOIUrl":null,"url":null,"abstract":"In this paper, the automatic order sorting problem with scattered storage is studied. First, the mathematical model of the problem is established. Then an improved crossover particle swarm optimization (CPSO) algorithm is proposed for order batching, batch sequencing and storage selection. The CPSO mainly conducts the position update of particle swarm optimization algorithm by using crossover, which makes it more suitable for discrete problems. In order to enhance the local search capability of the algorithm, a variable neighborhood search (VNS) algorithm is proposed. And the neighborhood structure of the automatic order sorting problem for scattered storage is defined. The VNS will further search the neighborhood of the global optimal solution after each operation of the CPSO position update. Finally, the effectiveness of the proposed CPSO is verified by numerical experiments.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA54519.2022.9856225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the automatic order sorting problem with scattered storage is studied. First, the mathematical model of the problem is established. Then an improved crossover particle swarm optimization (CPSO) algorithm is proposed for order batching, batch sequencing and storage selection. The CPSO mainly conducts the position update of particle swarm optimization algorithm by using crossover, which makes it more suitable for discrete problems. In order to enhance the local search capability of the algorithm, a variable neighborhood search (VNS) algorithm is proposed. And the neighborhood structure of the automatic order sorting problem for scattered storage is defined. The VNS will further search the neighborhood of the global optimal solution after each operation of the CPSO position update. Finally, the effectiveness of the proposed CPSO is verified by numerical experiments.