Memetic algorithms in dynamic environments
Min Huang · Control theory & applications · 2010
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.