协同进化数值优化算法

计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (33): 39-42.

协同进化数值优化算法

彭复明

南京工业职业技术学院计算机与软件学院，南京 210046

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-11-21 发布日期:2011-11-21

Coevolutionary algorithm for numerical optimization

PENG Fuming

College of Computer and Software，Nanjing Institute of Industry Technology，Nanjing 210046，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-11-21 Published:2011-11-21

摘要/Abstract

摘要： 为了提高进化算法的全局收敛性，提出了一种多种群同时进化的算法。根据生物学基因的多样性理论，新算法保持单个种群的相对纯洁性与整个群体繁殖方式的丰富性，不同的种群采用不同的算子，并在不同的生境繁衍后代，目的是保持种群基因的多样性。当算法陷入局部最优解领域时，可用逆向优化寻找对偶个体，使算法走出局部最优解空间。实验结果表明，在与多组优化数据的比较中，新算法在所有单项与综合项目上全部名列第一。

关键词: 基因多样性, 配子, 育种口径, 线生境, 对偶个体, 逆向优化

Abstract: To improve the global astringency of evolutionary algorithm，an algorithm based on multi-population concurrent evolution is proposed.According to the biological genetic diversity theory，the new algorithm maintains a single population’s relative purity and the whole population’s richness of breeding way.Different operators are used for different populations which breed in different habitats，so as to keep the diversity of population genes.When the algorithm is entrapped into a local optimal solution field，the reverse optimization can be applied to seek for its antithesis individuals to lift it out of the local optimal solution field.The experimental result shows that the new algorithm ranks first in all single and comprehensive items in comparison with a group of optimization data.

Key words: genetic diversity, gamete, breeding caliber, line habitat, antithesis individual, reverse optimization

彭复明. 协同进化数值优化算法[J]. 计算机工程与应用, 2011, 47(33): 39-42.

PENG Fuming. Coevolutionary algorithm for numerical optimization[J]. Computer Engineering and Applications, 2011, 47(33): 39-42.