一种基于混沌领域搜索的自适应遗传算法  

Chaos neighborhood-based self-adaptive genetic algorithm

作　　者：魏明[1] 蔡延光[1] 

机构地区：[1]广东工业大学自动化学院,广州510090

出　　处：《计算机应用研究》2009年第2期464-465,共2页Application Research of Computers

基　　金：国家自然科学基金资助项目(60374062);广东省科技计划资助项目(2005B10101015;2007B010200070)

摘　　要：提出一种基于混沌领域搜索的自适应混沌遗传算法,该方法在遗传进化的过程根据种群相对多样性对每代个体引入混沌领域方法搜索有效基因,并有效地结合遗传算法善于全局优化和混沌局部搜索能力强等特点。计算结果表明,该算法可以显著提高计算效率,具有较大的实用价值。This paper proposed a chaos neighborhood-based self-adaptive genetic algorithm(CNSAGA) to combine the chaos optimization with standard genetic algorithm effectively together.Differing from other conventional chaos genetic hybrid algorithms,the algorithm proposed a chaos neighborhood operator was introduced in the evolution process to find best gene according to the measure of species diversity.The research shows that CNSAGA can achieve satisfactory optimization results.

关 键 词：遗传算法 混沌优化 旅行商问题 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]