{"title":"遗传算法在动态交通分配中的应用","authors":"Runmei Li, Wei Li","doi":"10.1109/IVS.2005.1505207","DOIUrl":null,"url":null,"abstract":"In this paper, the applications of genetic algorithms to dynamic traffic assignment are analyzed based on a dynamic traffic assignment variational inequality model and the condition of physical queue is studied in this model. A simple example is used to demonstrate the efficiency of the genetic algorithms. The conclusions and directions for future development about the application of genetic algorithm to traffic assignment are presented.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The application of genetic algorithm to dynamic traffic assignment\",\"authors\":\"Runmei Li, Wei Li\",\"doi\":\"10.1109/IVS.2005.1505207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the applications of genetic algorithms to dynamic traffic assignment are analyzed based on a dynamic traffic assignment variational inequality model and the condition of physical queue is studied in this model. A simple example is used to demonstrate the efficiency of the genetic algorithms. The conclusions and directions for future development about the application of genetic algorithm to traffic assignment are presented.\",\"PeriodicalId\":386189,\"journal\":{\"name\":\"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2005.1505207\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2005.1505207","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of genetic algorithm to dynamic traffic assignment
In this paper, the applications of genetic algorithms to dynamic traffic assignment are analyzed based on a dynamic traffic assignment variational inequality model and the condition of physical queue is studied in this model. A simple example is used to demonstrate the efficiency of the genetic algorithms. The conclusions and directions for future development about the application of genetic algorithm to traffic assignment are presented.
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