Memetic algorithms in dynamic environments
动态环境中的Memetic算法

Based on particle swarm optimization(PSO), we propose a memetic algorithm for solving dynamic optimization problems which are widely concerned from the evolutionary computation community. In this algorithm, a fuzzy cognition local search method is employed for improving the quality of individuals and a self-organized random immigrant scheme is used to further enhance the exploration capacity in a local version of PSO with a ring-shape topology structure. Experimental study over a series of dynamic test benchmark problems shows that the proposed PSO-based Memetic algorithm is robust and adaptable in the dynamic environments.