{"title":"求解多车场车辆路径问题的元启发式算法","authors":"Omar M. Khairy, Omar M. Shehata, E. I. Morgan","doi":"10.1109/NILES50944.2020.9257879","DOIUrl":null,"url":null,"abstract":"Multi-depot Vehicle Routing Problem is one of the most important and challenging variations of the classical Vehicle Routing Problem, where the goal is to find the routes for a fleet of vehicles to serve a number of customers, travelling from and to several depots. Due to the complexity of solving such problems, meta-heuristic algorithms are used. The Most Valuable Player algorithm is a recent technique used to solve continuous optimization problems. This study uses the Genetic Algorithm and the Ant Colony Optimization to solve the Multi-Depot Vehicle Routing Problem. A Hybrid Most Valuable Player algorithm is also proposed to solve the multi-depot vehicle routing problem. The algorithm was tested on 10 different problems and compared to two well-known techniques, Genetic Algorithm and Ant Colony Optimization. Results of the developed algorithm were satisfactory for small sized problems, however Genetic Algorithm surpassed both other algorithms in most test cases.","PeriodicalId":253090,"journal":{"name":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Meta-heuristic Algorithms for Solving the Multi-Depot Vehicle Routing Problem\",\"authors\":\"Omar M. Khairy, Omar M. Shehata, E. I. Morgan\",\"doi\":\"10.1109/NILES50944.2020.9257879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-depot Vehicle Routing Problem is one of the most important and challenging variations of the classical Vehicle Routing Problem, where the goal is to find the routes for a fleet of vehicles to serve a number of customers, travelling from and to several depots. Due to the complexity of solving such problems, meta-heuristic algorithms are used. The Most Valuable Player algorithm is a recent technique used to solve continuous optimization problems. This study uses the Genetic Algorithm and the Ant Colony Optimization to solve the Multi-Depot Vehicle Routing Problem. A Hybrid Most Valuable Player algorithm is also proposed to solve the multi-depot vehicle routing problem. The algorithm was tested on 10 different problems and compared to two well-known techniques, Genetic Algorithm and Ant Colony Optimization. Results of the developed algorithm were satisfactory for small sized problems, however Genetic Algorithm surpassed both other algorithms in most test cases.\",\"PeriodicalId\":253090,\"journal\":{\"name\":\"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NILES50944.2020.9257879\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NILES50944.2020.9257879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Meta-heuristic Algorithms for Solving the Multi-Depot Vehicle Routing Problem
Multi-depot Vehicle Routing Problem is one of the most important and challenging variations of the classical Vehicle Routing Problem, where the goal is to find the routes for a fleet of vehicles to serve a number of customers, travelling from and to several depots. Due to the complexity of solving such problems, meta-heuristic algorithms are used. The Most Valuable Player algorithm is a recent technique used to solve continuous optimization problems. This study uses the Genetic Algorithm and the Ant Colony Optimization to solve the Multi-Depot Vehicle Routing Problem. A Hybrid Most Valuable Player algorithm is also proposed to solve the multi-depot vehicle routing problem. The algorithm was tested on 10 different problems and compared to two well-known techniques, Genetic Algorithm and Ant Colony Optimization. Results of the developed algorithm were satisfactory for small sized problems, however Genetic Algorithm surpassed both other algorithms in most test cases.