Improving the non-dominate sorting genetic algorithm for multi-objective optimization

被引:8
作者
Ghomsheh, V. Seydi
Khanehsar, M. Ahmadieh
Teshnehlab, M.
机构
来源
CIS WORKSHOPS 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY WORKSHOPS | 2007年
关键词
D O I
10.1109/CIS.Workshops.2007.192
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 [10]. 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.
引用
收藏
页码:89 / 92
页数:4
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