计算机应用研究2016，Vol.33Issue(8)：2350-2352,2362,4.DOI:10.3969/j.issn.1001-3695.2016.08.025
一种基于博弈论的混合优化算法
Hybrid optimization algorithm based on game theory
摘要
Abstract
In order to overcome the innate drawbacks and limitations of a single swarm intelligence optimization algorithm,this paper proposed a multiple sub-swarms—multiple strategies hybrid optimization algorithm based on game theory.Firstly,each sub-swarm chose the best strategies by pay utility matrix.Secondly,each sub-swarm in the best strategies to search optimiza-tion independently,it made the sub-swarm dynamically adapt to the changes in the searching process.Finally,with pair-wise combinations of CS,PSO and DE,this paper put forward the algorithms of CS-PSO,DE-PSO and DE-CS to test the perform-ance of hybrid optimization algorithm.Simulation experiments show that when the single optimization algorithm had different search features,the hybrid optimization algorithm has a higher ability of searching optimization and convergence efficiency.关键词
群智能优化算法/混合算法/博弈论/支付效用矩阵/最优策略Key words
swarm intelligence algorithm/hybrid algorithm/game theory/pay utility matrix/best strategies分类
信息技术与安全科学引用本文复制引用
杨梅,刘坚..一种基于博弈论的混合优化算法[J].计算机应用研究,2016,33(8):2350-2352,2362,4.基金项目
国家自然科学基金资助项目（71271078）；湖南省战略新兴产业重大专项资助项目（2013GK4049）；长沙市科技重大专项资助项目 （）
