摘要
将熵的概念引入共享机制小生境技术,提出了一种基于小生境熵的自适应混合遗传算法。通过自适应调整小生境半径,改进了共享机制在算法中的作用,提出了用以度量种群多样性的小生境熵的概念。算法通过种群所处的进化世代数及该世代种群的小生境熵,实现了进化参数(交叉、变异概率)的自适应调整。证明了该算法具有强全局收敛性。实验表明,该算法对于解决多模态函数优化问题,具有很好的全局搜索能力和较快的收敛速度。
A niche entropy-based adaptive hybrid genetic algorithm is proposed, which introduces entropy into the niching method of sharing scheme. Niching radius can be adjusted adaptively in the algorithm in order to improve the sharing scheme, and concept of niche entropy is put forth to measure population＇s diversity. Evolutionary parameters of crossover probability and mutation probability can also be adjusted adaptively on the basis of the evolutionary generation number and the niche entropy of the population in that generation. The strong global convergence of the algorthm is demonstrated in this paper, and experiments show that the algorithm can solve those multimodal function optimization problems with good global search ability and fast convergence rate.
出处
《中国管理科学》
CSSCI
2008年第2期115-121,共7页
Chinese Journal of Management Science
基金
国家自然科学基金重点资助项目(70631003)
国家自然科学基金资助项目(70771037)
教育部重点研究项目(107067)
关键词
混合遗传算法
小生境熵
共享机制
多模态函数优化
hybrid genetic algorithm
niche entropy
sharing scheme
multimodal function optimization
