{"title":"无人快递车辆多目的地配送路线优化研究","authors":"Shushang Chi, Pengying Du, Jingjing Huang","doi":"10.1109/ICSAI48974.2019.9010559","DOIUrl":null,"url":null,"abstract":"Unmanned express vehicles play an increasingly important role in the logistics industry. In order to save time, reduce transportation costs in the process of logistics and distribution, and improve the utilization of resources, it is necessary to optimize the path of unmanned express vehicles to achieve the shortest logistics path in multiple destinations. Using the hybrid particle swarm optimization algorithm based on particle swarm optimization and genetic algorithm to optimize the path and overcome the long iteration of genetic algorithm could obtain a better optimal solution with fewer iterations, and the optimal solution is more stable. This can reduce the path mileage of logistics and transportation, improve work efficiency and reduce transportation time and cost.","PeriodicalId":270809,"journal":{"name":"2019 6th International Conference on Systems and Informatics (ICSAI)","volume":"103 10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research On Multi-destination Delivery Route Optimization Of Unmanned Express Vehicles\",\"authors\":\"Shushang Chi, Pengying Du, Jingjing Huang\",\"doi\":\"10.1109/ICSAI48974.2019.9010559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unmanned express vehicles play an increasingly important role in the logistics industry. In order to save time, reduce transportation costs in the process of logistics and distribution, and improve the utilization of resources, it is necessary to optimize the path of unmanned express vehicles to achieve the shortest logistics path in multiple destinations. Using the hybrid particle swarm optimization algorithm based on particle swarm optimization and genetic algorithm to optimize the path and overcome the long iteration of genetic algorithm could obtain a better optimal solution with fewer iterations, and the optimal solution is more stable. This can reduce the path mileage of logistics and transportation, improve work efficiency and reduce transportation time and cost.\",\"PeriodicalId\":270809,\"journal\":{\"name\":\"2019 6th International Conference on Systems and Informatics (ICSAI)\",\"volume\":\"103 10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 6th International Conference on Systems and Informatics (ICSAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAI48974.2019.9010559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI48974.2019.9010559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research On Multi-destination Delivery Route Optimization Of Unmanned Express Vehicles
Unmanned express vehicles play an increasingly important role in the logistics industry. In order to save time, reduce transportation costs in the process of logistics and distribution, and improve the utilization of resources, it is necessary to optimize the path of unmanned express vehicles to achieve the shortest logistics path in multiple destinations. Using the hybrid particle swarm optimization algorithm based on particle swarm optimization and genetic algorithm to optimize the path and overcome the long iteration of genetic algorithm could obtain a better optimal solution with fewer iterations, and the optimal solution is more stable. This can reduce the path mileage of logistics and transportation, improve work efficiency and reduce transportation time and cost.