族群进化算法

Ethnic Group Evolution Algorithm

借鉴人类学研究中族群的概念以及以族群为视角来分析群体的结构及其演变趋势的方法,提出了一种简单、有效的群体结构调控技术——族群机制.设计了针对二进制编码方式的族群分类方法,并基于该族群结构形成了具有双轨协同进化特征的族群进化算法以及相应的族群算子.针对高维函数和复杂混合函数的数值优化实验表明,族群进化机制可以显著提高群体的抗早熟能力和搜索效率,与其他典型算法的对比也表明,族群进化算法是一种具有竞争力的函数优化算法.

Enlightened by the conception of ethnic group in social science and a perspective to analyze the structure and evolutionary tendency of population in terms of ethnic group, a population structured technology, ethnic group mechanism, is proposed. Meanwhile, an ethnic group evolution algorithm （EGEA） with a dual track co-evolution process and special ethnic group operators is designed for binary coding. The simulation tests of the classical function and challenging composition test function show that the EGEA can restrain premature convergence effectively during the evolutionary process while improving the search efficiency greatly. The comparisons between EGEA and other typical algorithm show EGEA is a competent algorithm for solving numerical optimization problems.