Application of self-organizing maps to genetic algorithms

被引：0

作者：

Kan, S. ^{[1
]}

Fei, Z. ^{[1
]}

Kita, E. ^{[1
]}

机构：

[1] Nagoya Univ, Grad Sch Informat Sci, Nagoya, Aichi 4648601, Japan

来源：

COMPUTER AIDED OPTIMUM DESIGN IN ENGINEERING XI | 2009年 / 106卷

关键词：

real-coded genetic algorithms; self-organizing maps; Rastrigin function;

D O I：

10.2495/OP090011

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper describes Self-Organizing Maps for Genetic Algorithm (SOM-GA). In this algorithm, the search performance of a real-coded genetic algorithm (RCGA) is enhanced with self-organizing map (SOM). The SOM is trained with the information of the individuals in the population. Sub-populations are generated from a whole population by the help of the map. The RCGA search is performed in the sub-populations. The Rastrigin function is considered as a test problem. The search performance of SOM-GA is compared with that of the RCGA. The results show that the use of the sub-population search algorithm improves the local search performance of the RCGA and therefore, SOM-GA can find better solutions in shorter CPU time than RCGA.

引用

页码：3 / 11

页数：9

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