针对传统单种群进化类算法(conventional evolutionary algorithms,简称CEAs)求解基因连锁问题的不足,基于生物界共同进化机制提出求解NK基因连锁问题的合作式共同进化算法(Coevolutionary algorithm,简称CoEA),探讨其子种群的合作方式与个体适应值的计算方法,并从数学上分析该算法的性能,指出共同进化算法中高于平均适应值模式的递增指数高于传统单种群进化算法.仿真结果证实了理论分析.结果表明,共同进化算法比传统单种群进化算法对求解基因连锁问题的效力和效

It is difficult for conventional single population-based evolutionary algorithms (conventionalevolutionary algorithms-CEAs) to solve epistatic interaction problems. Based on computational model ofcooperative coevolution inspired by the coevolutionary phenomena of natural species, a coevolutionary algorithm (CoEA) for solving NK-landscape. problem is proposed. Some problems related to the interactions among species and individual s fitness computation are discussed. Mathematical analysis shows that the exponential increase. index of CoEA is higher than that of CEA for a schema which fitness is higher than the average fitness of population.Simulation results verify the theoretical result,and show that the coevolutionary algorithm is more efficient and effective than CEA in solving epistatic interactions problems.

国家自然科学基金资助项目(69903010,69933030)