{"title":"基于模拟退火的多目标遗传算法","authors":"Tang Xin-Hua, Chang Xu, Fang Zhifeng","doi":"10.1109/MINES.2012.34","DOIUrl":null,"url":null,"abstract":"Combined the characteristic of simulated annealing, we propose a multi-objective genetic algorithm based on simulated annealing. We take the advantage of simulated annealing, improve the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm. Experimental results show that the improved algorithm improve the solution efficiency of the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm effectively.","PeriodicalId":208089,"journal":{"name":"2012 Fourth International Conference on Multimedia Information Networking and Security","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Multi-objective Genetic Algorithm Based on Simulated Annealing\",\"authors\":\"Tang Xin-Hua, Chang Xu, Fang Zhifeng\",\"doi\":\"10.1109/MINES.2012.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Combined the characteristic of simulated annealing, we propose a multi-objective genetic algorithm based on simulated annealing. We take the advantage of simulated annealing, improve the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm. Experimental results show that the improved algorithm improve the solution efficiency of the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm effectively.\",\"PeriodicalId\":208089,\"journal\":{\"name\":\"2012 Fourth International Conference on Multimedia Information Networking and Security\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Multimedia Information Networking and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MINES.2012.34\",\"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 Multimedia Information Networking and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MINES.2012.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-objective Genetic Algorithm Based on Simulated Annealing
Combined the characteristic of simulated annealing, we propose a multi-objective genetic algorithm based on simulated annealing. We take the advantage of simulated annealing, improve the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm. Experimental results show that the improved algorithm improve the solution efficiency of the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm effectively.