基于自适应K均值聚类的小生境遗传算法

Niche Genetic Algorithm Based on Self-Adaptive K Means Clustering Fitness Sharing

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.