{"title":"多目标粒子群优化中优区控制分析","authors":"A. B. Carvalho, A. Pozo","doi":"10.1109/HIS.2010.5600088","DOIUrl":null,"url":null,"abstract":"The interest in the application of particle swarm optimization to solve different problems, especially multi-objective problems, grew in recent years. This metaheuristic is particularly suitable to solve real life problems, but like other multi-objective metaheuristics, has some limitations when dealing with problems with many objectives, typically more than three. Recently, some many-objective techniques were proposed to avoid the deterioration of the search ability of Pareto dominance based multi-objective evolutionary algorithms for many-objective problems. This work presents a study of the influence of the many-objective technique called the control of dominance area of solutions (CDAS) in multi-objective particle swarm optimization. It is presented an empirical analysis to identify the influence of the CDAS technique on the convergence and the diversity of a multi-objective PSO algorithm in many-objective scenarios through the analysis of some quality indicators and statistical tests.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analyzing the control of dominance area of solutions in particle swarm optimization for many-objective\",\"authors\":\"A. B. Carvalho, A. Pozo\",\"doi\":\"10.1109/HIS.2010.5600088\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The interest in the application of particle swarm optimization to solve different problems, especially multi-objective problems, grew in recent years. This metaheuristic is particularly suitable to solve real life problems, but like other multi-objective metaheuristics, has some limitations when dealing with problems with many objectives, typically more than three. Recently, some many-objective techniques were proposed to avoid the deterioration of the search ability of Pareto dominance based multi-objective evolutionary algorithms for many-objective problems. This work presents a study of the influence of the many-objective technique called the control of dominance area of solutions (CDAS) in multi-objective particle swarm optimization. It is presented an empirical analysis to identify the influence of the CDAS technique on the convergence and the diversity of a multi-objective PSO algorithm in many-objective scenarios through the analysis of some quality indicators and statistical tests.\",\"PeriodicalId\":174618,\"journal\":{\"name\":\"2010 10th International Conference on Hybrid Intelligent Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 10th International Conference on Hybrid Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2010.5600088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 10th International Conference on Hybrid Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2010.5600088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing the control of dominance area of solutions in particle swarm optimization for many-objective
The interest in the application of particle swarm optimization to solve different problems, especially multi-objective problems, grew in recent years. This metaheuristic is particularly suitable to solve real life problems, but like other multi-objective metaheuristics, has some limitations when dealing with problems with many objectives, typically more than three. Recently, some many-objective techniques were proposed to avoid the deterioration of the search ability of Pareto dominance based multi-objective evolutionary algorithms for many-objective problems. This work presents a study of the influence of the many-objective technique called the control of dominance area of solutions (CDAS) in multi-objective particle swarm optimization. It is presented an empirical analysis to identify the influence of the CDAS technique on the convergence and the diversity of a multi-objective PSO algorithm in many-objective scenarios through the analysis of some quality indicators and statistical tests.