Improved multi-objective diversity control oriented genetic algorithm

被引:0
|
作者
Piroonratana, Theera
Chaiyaratana, Nachol
机构
[1] Kings Mongkuts Inst Technol N Bangkok, Dept Prod Engn, Bangkok 10800, Thailand
[2] Kings Mongkuts Inst Technol N Bangkok, Res & Dev Ctr Intelligent Syst, Bangkok 10800, Thailand
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an improved multi-objective diversity control oriented genetic algorithm (MODCGA-II). The improvement includes the introduction of an objective-domain diversity control operator, which is chromosome representation independent, and a solution archive. The performance comparison between the MODCGA-II, a non-dominated sorting genetic algorithm II (NSGA-II) and an improved strength Pareto evolutionary algorithm (SPEA-II) is carried out where different two-objective benchmark problems with specific multi-objective characteristics are utilised. The results indicate that the MODCGA-II solutions are better than the solutions generated by the NSGA-II and SPEA-II in terms of the closeness to the true Pareto optimal solutions and the uniformity of solution distribution along the Pareto front.
引用
收藏
页码:430 / 439
页数:10
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