{"title":"最大独立集问题的精英遗传算法","authors":"A. Taranenko, A. Vesel","doi":"10.1109/ITI.2001.938044","DOIUrl":null,"url":null,"abstract":"Genetic algorithms are a computational paradigm belonging to the class of optimization techniques known as evolutionary computation. They have been implemented successfully to solve many difficult optimization problems. We have developed a new genetic algorithm for the maximum independent set problem based on the elitist strategy. The algorithm presented is tested on the so-called DIMACS benchmark graphs. The effectiveness of the algorithm is very satisfactory since it outperforms in most cases the genetic algorithms for the maximum independent set problem reported in the literature.","PeriodicalId":375405,"journal":{"name":"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An elitist genetic algorithm for the maximum independent set problem\",\"authors\":\"A. Taranenko, A. Vesel\",\"doi\":\"10.1109/ITI.2001.938044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Genetic algorithms are a computational paradigm belonging to the class of optimization techniques known as evolutionary computation. They have been implemented successfully to solve many difficult optimization problems. We have developed a new genetic algorithm for the maximum independent set problem based on the elitist strategy. The algorithm presented is tested on the so-called DIMACS benchmark graphs. The effectiveness of the algorithm is very satisfactory since it outperforms in most cases the genetic algorithms for the maximum independent set problem reported in the literature.\",\"PeriodicalId\":375405,\"journal\":{\"name\":\"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITI.2001.938044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd International Conference on Information Technology Interfaces, 2001. ITI 2001.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITI.2001.938044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An elitist genetic algorithm for the maximum independent set problem
Genetic algorithms are a computational paradigm belonging to the class of optimization techniques known as evolutionary computation. They have been implemented successfully to solve many difficult optimization problems. We have developed a new genetic algorithm for the maximum independent set problem based on the elitist strategy. The algorithm presented is tested on the so-called DIMACS benchmark graphs. The effectiveness of the algorithm is very satisfactory since it outperforms in most cases the genetic algorithms for the maximum independent set problem reported in the literature.