{"title":"基于改进遗传算法的最短路径问题研究","authors":"Zongyan Xu, Haihua Li, Ye Guan","doi":"10.1109/ICCIS.2012.52","DOIUrl":null,"url":null,"abstract":"This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.","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":"5","resultStr":"{\"title\":\"A Study on the Shortest Path Problem Based on Improved Genetic Algorithm\",\"authors\":\"Zongyan Xu, Haihua Li, Ye Guan\",\"doi\":\"10.1109/ICCIS.2012.52\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.\",\"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\":\"5\",\"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.2012.52\",\"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.2012.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study on the Shortest Path Problem Based on Improved Genetic Algorithm
This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.