关键词: 遗传算法, 聚类分析, K-means算法

Abstract: An improved clustering approach is described in this paper.The traditional K-means algorithm is good at locally searching capability，but it is sensitive to the initialization，easy to get stuck at locally optimal values.The simple genetic algorithm-based clustering method is a global optimize approach，but it is weak at the locally searching capability and convergence speed.Take the problems which exists in the two algorithms into account，a new clustering algorithm is put forwarded in this paper.The new approach integrates the advantages of the two algorithms，which introduces the K-means operation and then utilizes the genetic algorithm to do some optimization and also improved the crossover operation in the genetic algorithm，improves the locally searching capability and convergence speed of the genetic algorithm-based clustering algorithm.

Key words: genetic algorithm, clustering analysis, K-means algorithm