Crowding Clustering Genetic Algorithm for Multimodal Function Optimization

For multimodal function optimization problems,this paper analyzes several niching strategies,combines the crowding model with the clustering algorithm,and proposes a crowding clustering genetic algorithm.Crowding model is used to form multiple niches in fitness landscape,while clustering algorithm eliminates genetic drift in each inner niche.Theoretical analysis proves the convergence property of the proposed algorithm.Numerical results indicate that crowding clustering model is superior to both crowding model and deterministic crowding model in(quantity,) quality and accuracy of multi-optima searching.The crowding clustering genetic algorithm has been applied to the varied-line-spacing holographic grating design in the National Synchrotron Radiation Laboratory,and achieves satisfactory results.