{"title":"车辆路径问题的混合行为蚁群算法","authors":"Miao Wang","doi":"10.1109/ICCIS.2012.168","DOIUrl":null,"url":null,"abstract":"Vehicle Routing Problem (VRP) is one of critical problems in modern logistics service. In order to overcome the shortcomings of the basic Ant Colony Optimization (ACO) algorithm, which has long searching time and easily jumps into local optimal solution, a hybrid behavior ACO algorithm is presented for solving the VRP problem. A series of rules of the ants' behaviors are defined. The simulation results show that the above approach is reasonable and efficient.","PeriodicalId":269967,"journal":{"name":"2012 Fourth International Conference on Computational and Information Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Hybrid Behavior Ant Colony Algorithm for Vehicle Routing Problem\",\"authors\":\"Miao Wang\",\"doi\":\"10.1109/ICCIS.2012.168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicle Routing Problem (VRP) is one of critical problems in modern logistics service. In order to overcome the shortcomings of the basic Ant Colony Optimization (ACO) algorithm, which has long searching time and easily jumps into local optimal solution, a hybrid behavior ACO algorithm is presented for solving the VRP problem. A series of rules of the ants' behaviors are defined. The simulation results show that the above approach is reasonable and efficient.\",\"PeriodicalId\":269967,\"journal\":{\"name\":\"2012 Fourth International Conference on Computational and Information Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Computational and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2012.168\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2012.168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid Behavior Ant Colony Algorithm for Vehicle Routing Problem
Vehicle Routing Problem (VRP) is one of critical problems in modern logistics service. In order to overcome the shortcomings of the basic Ant Colony Optimization (ACO) algorithm, which has long searching time and easily jumps into local optimal solution, a hybrid behavior ACO algorithm is presented for solving the VRP problem. A series of rules of the ants' behaviors are defined. The simulation results show that the above approach is reasonable and efficient.
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