{"title":"研究模糊信息下的车辆调度问题","authors":"Lu Lin","doi":"10.1109/ICSSSM.2009.5174874","DOIUrl":null,"url":null,"abstract":"To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.","PeriodicalId":287881,"journal":{"name":"2009 6th International Conference on Service Systems and Service Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study vehicle scheduling sever problem under fuzzy information\",\"authors\":\"Lu Lin\",\"doi\":\"10.1109/ICSSSM.2009.5174874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.\",\"PeriodicalId\":287881,\"journal\":{\"name\":\"2009 6th International Conference on Service Systems and Service Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 6th International Conference on Service Systems and Service Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSSM.2009.5174874\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 6th International Conference on Service Systems and Service Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2009.5174874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study vehicle scheduling sever problem under fuzzy information
To solve the vehicle scheduling sever problem under fuzzy information, the paper takes vehicle's fuzzy travel time and customer's fuzzy due time as fuzzy information parameter and uses the method of subdividing the customer's class to absorb the carriers' knowledge system, builds two deciding-making goals of logistic enterprises' utility maximization and customers' s utility maximization to two kinds of fuzzy information dynamic vehicle scheduling model, and proposes ant colony optimization method to solve this problem. The artificial test analyzes the influence of the computed results of these two kinds of models with the change of policy-making parameters and suggests the frame basis of correlation parameters of the formulation.