{"title":"一种改进的变异算子,可提高遗传算法的性能","authors":"Yingying Song, Feifei Yan","doi":"10.1109/icaice54393.2021.00025","DOIUrl":null,"url":null,"abstract":"An improved combined mutation operator (CM) is proposed for the problems of premature convergence and local optimization which often occur in genetic algorithm (GA). The CM operator combines the Gaussian mutation and the initial mutation to perform local initialization operations on individuals in the population, and maintain the population diversity while improving the local search ability of the operator. The results of 15 benchmark optimization problems show that the proposed CM operator can effectively improve the performance of the algorithm, and compared with other advanced algorithms, the improved algorithm (IRCGA) has stronger search capabilities and faster convergence speed.","PeriodicalId":388444,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Mutation Operator Which Can Improve the Performance of Genetic Algorithm\",\"authors\":\"Yingying Song, Feifei Yan\",\"doi\":\"10.1109/icaice54393.2021.00025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved combined mutation operator (CM) is proposed for the problems of premature convergence and local optimization which often occur in genetic algorithm (GA). The CM operator combines the Gaussian mutation and the initial mutation to perform local initialization operations on individuals in the population, and maintain the population diversity while improving the local search ability of the operator. The results of 15 benchmark optimization problems show that the proposed CM operator can effectively improve the performance of the algorithm, and compared with other advanced algorithms, the improved algorithm (IRCGA) has stronger search capabilities and faster convergence speed.\",\"PeriodicalId\":388444,\"journal\":{\"name\":\"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icaice54393.2021.00025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icaice54393.2021.00025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Mutation Operator Which Can Improve the Performance of Genetic Algorithm
An improved combined mutation operator (CM) is proposed for the problems of premature convergence and local optimization which often occur in genetic algorithm (GA). The CM operator combines the Gaussian mutation and the initial mutation to perform local initialization operations on individuals in the population, and maintain the population diversity while improving the local search ability of the operator. The results of 15 benchmark optimization problems show that the proposed CM operator can effectively improve the performance of the algorithm, and compared with other advanced algorithms, the improved algorithm (IRCGA) has stronger search capabilities and faster convergence speed.