Analysis of complete convergence for genetic algorithm with immune memory

被引：0
|
作者：
Zheng, SQ [1 ]
Yang, KY
Wang, XF
机构：
[1] Nankai Univ, Coll Informat Technol & Sci, Tianjin 300071, Peoples R China
[2] Shandong Inst Architecture & Engn, Coll Informat & Elect Engn, Jinan 250101, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 2, PROCEEDINGS | 2005年 / 3611卷
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：
A new Immune Memory Genetic Algorithm (IMGA) based on the mechanism of immune memory and immune network is proposed in this article. Using Markov chains theory, we proven that NGA(Niche Genetic Algorithms) can't not be complete convergence but IMGA can. The contrast simulation experiments between NGA and IMGA are performed. The experiments results validate the theoretical analysis and testify that IMGA has availability on solving multi-modal optimization problems, with quickly convergence ability and wonderful stability.
引用
收藏
页码：978 / 982
页数：5
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