关键词: 遗传算法, 小生境技术, 聚类分析, 早熟收敛

Abstract: To solve the premature convergence of the standard genetic algorithm and improve its local convergence ability, a new clustering genetic algorithm based on the complex method is proposed in this paper. The traditional genetic algorithm is improved by using the complex method and clustering niche technique. A clustering genetic algorithm（NCGA）based on complex method is obtained. The algorithm is programmed using FORTRAN language, and its performance is tested by using three kinds of complex test functions, and the performance comparison of the Adaptive Genetic Algorithm（AGA）is carried out. It also analyzes the influence of the initial population’s quality on the performance of the algorithm. Test results show that the improvement effect of genetic algorithm is obvious. The local search ability of the genetic algorithm can be significantly enhanced by the integration of complex operation in genetic algorithm. And the global search ability of genetic algorithm is significantly enhanced after using clustering technique. The stability of the algorithm is enhanced by the addition of backward learning operation. The improved genetic algorithm is better than the traditional genetic algorithm.

Key words: genetic algorithm, niche technique, clustering analysis, early convergence