Chu-Xuan Huai, Guo-hua Sun, Ranwen Qu, Z. Gao, Zehao Zhang
{"title":"Vehicle Routing Problem with Multi-type Vehicles in the Cold Chain Logistics System","authors":"Chu-Xuan Huai, Guo-hua Sun, Ranwen Qu, Z. Gao, Zehao Zhang","doi":"10.1109/ICSSSM.2019.8887612","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-objective model aiming to minimize both distribution cost and cargo damage cost is constructed to study the vehicle routing problem (VRP) with multi-type vehicles in the cold chain logistics system. Since VRP is an NP-hard problem, the optimal solutions cannot be obtained in a short time with exact algorithms as the scale increases. The genetic algorithms based on two decoding methods giving the priority to capacity and cargo damage are designed to solve the problem. The algorithm is applied to solve the distribution problem of H logistics company and the results obtained with two decoding methods are compared.","PeriodicalId":442421,"journal":{"name":"2019 16th International Conference on Service Systems and Service Management (ICSSSM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 16th International Conference on Service Systems and Service Management (ICSSSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2019.8887612","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, a multi-objective model aiming to minimize both distribution cost and cargo damage cost is constructed to study the vehicle routing problem (VRP) with multi-type vehicles in the cold chain logistics system. Since VRP is an NP-hard problem, the optimal solutions cannot be obtained in a short time with exact algorithms as the scale increases. The genetic algorithms based on two decoding methods giving the priority to capacity and cargo damage are designed to solve the problem. The algorithm is applied to solve the distribution problem of H logistics company and the results obtained with two decoding methods are compared.