This paper proposed a co-evolutionary genetic algorithm by two stages based on potential field. In the first stage;each population was evolved mainly by sexual reproduction? When all populations reached evolutionary stagnate;key areas were formed by cluster analysis;and narrowing the search area can improve the efficiency of the algorithm. In the second stage;each population was evolved mainly by asexual reproduction to enhance local search;and realized the directed evolution based on individuals;fitness so as to speed up the convergence rate. At the same time it proposed a concept called environmental potential field which could guide the evolution in order to make multiple populations evolve cooperatively. The experimental results show that the proposed algorithm has high quality of precision and rapid conver gence rate and that it overcomes the low efficiency of traditional algorithms to some extent.%提出一种基于势场引导的两阶段协同进化遗传算法.第一阶段,各种群以有性繁殖为主进化,各种群进化停滞时,通过聚类形成重点搜索区域,缩小了搜索区域,提高了算法效率；第二阶段,各种群以无性繁殖为主进化,加强局部搜索,实现了基于个体适应度的定向进化,提高了算法收敛速度.同时,为了指导种群进化,实现种群间的协同,将环境势场引入至两阶段协同进化过程中.仿真实验表明,该算法具有精度高、收敛速度快等优点,一定程度上克服了目前进化算法的搜索低效性.
展开▼
