{"title":"模糊需求下车辆路径问题的混合启发式算法","authors":"Changshi Liu, F. Huang","doi":"10.1109/CSO.2010.35","DOIUrl":null,"url":null,"abstract":"The vehicle routing problem with fuzzy demand at nodes is considered in this paper. The fuzzy possibility calculation approaches are presented to determine the preference strength to send the vehicle to next node, and the hybrid heuristics is proposed to determine a set of vehicle routes that minimizes vehicle number and total costs. Finally the computational results are presented to show the high effectiveness and performance of the solution approaches.","PeriodicalId":427481,"journal":{"name":"2010 Third International Joint Conference on Computational Science and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Hybrid Heuristics for Vehicle Routing Problem with Fuzzy Demands\",\"authors\":\"Changshi Liu, F. Huang\",\"doi\":\"10.1109/CSO.2010.35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The vehicle routing problem with fuzzy demand at nodes is considered in this paper. The fuzzy possibility calculation approaches are presented to determine the preference strength to send the vehicle to next node, and the hybrid heuristics is proposed to determine a set of vehicle routes that minimizes vehicle number and total costs. Finally the computational results are presented to show the high effectiveness and performance of the solution approaches.\",\"PeriodicalId\":427481,\"journal\":{\"name\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2010.35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Joint Conference on Computational Science and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2010.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid Heuristics for Vehicle Routing Problem with Fuzzy Demands
The vehicle routing problem with fuzzy demand at nodes is considered in this paper. The fuzzy possibility calculation approaches are presented to determine the preference strength to send the vehicle to next node, and the hybrid heuristics is proposed to determine a set of vehicle routes that minimizes vehicle number and total costs. Finally the computational results are presented to show the high effectiveness and performance of the solution approaches.
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