On the convergence of multi-parent genetic algorithms

被引：0
|
作者：
Ting, CK [1 ]
机构：
[1] Univ Gesamthsch Paderborn, Int Grad Sch Dynam Intelligent Syst, D-33100 Paderborn, Germany
来源：
2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS | 2005年
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 a Markov model for the convergence of multi-parent genetic algorithms (MPGAs). The proposed model formulates the variation of gene frequency caused by selection, multi-parent crossover, and mutation. In addition, it reveals the pairwise equivalence phenomenon in the number of parents. and identifies the correlation between this number and the mean fitness in the OneMax problem. The good fit between theoretical and experimental results demonstrate the capability of this model. Moreover, the superiority of multiparent crossover in convergence fitness over 2-parent crossover is validated theoretically as well as empirically.
引用
收藏
页码：396 / 403
页数：8
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