{"title":"Improving the Non-dominate Sorting Genetic Algorithm for Multi-objective Optimization","authors":"V. S. Ghomsheh, M.A. Khanehsar, M. Teshnehlab","doi":"10.1109/CIS.WORKSHOPS.2007.192","DOIUrl":null,"url":null,"abstract":"The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II) is proposed. This algorithm uses new method after non-dominate sorting procedure for keeping diversity. The comparison of n-NSGA-II with NSGA-II and other methods on ZDT test problems yields promising results.","PeriodicalId":409737,"journal":{"name":"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.WORKSHOPS.2007.192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II) is proposed. This algorithm uses new method after non-dominate sorting procedure for keeping diversity. The comparison of n-NSGA-II with NSGA-II and other methods on ZDT test problems yields promising results.
非支配排序遗传算法- ii (NSGA-II)是一种相对较新的技术,用于寻找或近似多目标优化问题的帕累托最优集。在不同的研究中,NSGA-II与其他多目标进化算法相比表现出了良好的性能(Deb et al., 2002)。本文提出了一个改进版本,命名为nicching - nsga - ii (n-NSGA-II)。该算法采用非支配排序后的新方法来保持多样性。n-NSGA-II与NSGA-II等方法对ZDT测试问题的比较得到了很好的结果。