摘要
在自适应小生境遗传算法的基础上,该文提出自适应K—均值聚类适应值共享小生境遗传算法。这种算法将聚类分析、自适应技术有机地结合起来,并且对于通常的K——均值聚类方法做了改进,即引进了一个最小聚类距离,通过调节最小聚类距离控制收敛到的小生境的数目,避免找到无效的极值点。这种算法不仅无需事先确定生境的具体数目和生境半径的大小,而且计算量小,搜索效率较高。
In the basement of studying on the fitness sharing genetic algorithms,method is proposed.The combination of the suggested method and the standard fitness sharing algorithms forms an integrated solution scheme for multimodal problems.The new algorithm made the improvement on the K means clustering method by introducing a minimal clustering distance which can control the number of the convergent peaks.There is no need to know the radius and the number of the peaks in advance for the improved algorithm.
出处
《电脑知识与技术》
2010年第9X期7676-7678,共3页
Computer Knowledge and Technology
关键词
多峰优化
小生境遗传算法
适应值共享算法
聚类算法
multimodal optimization
niche genetic algorithms
fitness sharing algorithms
clustering algorithms