{"title":"Research of Order Batching Variable Neighborhood Search Algorithm based on Saving Mileage","authors":"Zeping Pei, Zhuan Wang, Yiwen Yang","doi":"10.2991/ICMEIT-19.2019.34","DOIUrl":null,"url":null,"abstract":"Basing on a picker-to-parts batch picking system of full container load, an order batching model takes picking equipment and commodity packaging volume into consideration is constructed, the objective of the model is to maximize the saving mileage. To solve the model, an order batching variable neighborhood search algorithm is proposed. With the data from a specific logistic center, a simulation experiment has been carried out. The results show that, the performance of VNS-Deco is superior to FCFS, SBBM and S&U-Deco under 4 different order pool situations, the total picking mileage optimized by VNS-Deco is reduced by 13.2%, 3.3% and 1.6% compared with FCFS, SBBM and S&U-Deco.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Basing on a picker-to-parts batch picking system of full container load, an order batching model takes picking equipment and commodity packaging volume into consideration is constructed, the objective of the model is to maximize the saving mileage. To solve the model, an order batching variable neighborhood search algorithm is proposed. With the data from a specific logistic center, a simulation experiment has been carried out. The results show that, the performance of VNS-Deco is superior to FCFS, SBBM and S&U-Deco under 4 different order pool situations, the total picking mileage optimized by VNS-Deco is reduced by 13.2%, 3.3% and 1.6% compared with FCFS, SBBM and S&U-Deco.
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