{"title":"基于k均值聚类和人工鱼群算法的车辆路径优化研究","authors":"De-gang Ji, Dong-mei Huang","doi":"10.1109/ICNC.2012.6234729","DOIUrl":null,"url":null,"abstract":"Vehicle Routing Problem(VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization(KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"136 1","pages":"1141-1145"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A research based on K-means clustering and Artificial Fish-Swarm Algorithm for the Vehicle Routing Optimization\",\"authors\":\"De-gang Ji, Dong-mei Huang\",\"doi\":\"10.1109/ICNC.2012.6234729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicle Routing Problem(VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization(KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.\",\"PeriodicalId\":87274,\"journal\":{\"name\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"volume\":\"136 1\",\"pages\":\"1141-1145\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2012.6234729\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2012.6234729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A research based on K-means clustering and Artificial Fish-Swarm Algorithm for the Vehicle Routing Optimization
Vehicle Routing Problem(VRP) is an important problem in logistic system. Because of its NP-hard property, it is difficult to get the optimal solution when the constrains are more. Aiming at the problem of logistics distribution vehicle routing optimization, this paper provide a composite algorithm based on the K-means clustering and the Artificial Fish-Swarm Algorithm for the vehicle routing optimization(KMAFA). The results indicate that the algorithm can reduce the input of the algorithm and improve the converging speed. The computational result shows that the results of composite algorithm for VRP are competitive.