An Improved Real-Coded Genetic Algorithm and Its Application

被引：1

作者：

ZhongLai WangPing YangDan Ling and Qiang Miao School of Mechatronics EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina ^{[610054
]}

机构：

来源：

Journal of Electronic Science and Technology of China | 2008年 / 01期

关键词：

Adaptive mutation; arithmetic cross-over; elitist strategy; genetic algorithm;

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：

Real-coded genetic algorithm(RGA)usually meets the demand of consecutive space problem.However,compared with simple genetic algorithm(SGA)RGA also has the inherent disadvantages such as prematurity and slow convergence when the solution is close to the optimum solution.This paper presents an improved real-coded genetic algorithm to increase the computation efficiency and avoid prematurity,especially in the optimization of multi-modal function.In this method,mutation operation and crossover operation are improved.Examples are given to demonstrate its com p utation efficiency and robustness.

引用

页码：43 / 46

页数：4