A clustering-based differential evolution for global optimization
Applied Soft Computing
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A hierarchical clustering genetic algorithm which used hierarchical clustering based fitness sharing method was designed. Special designed inner-species selection and inner-species/inter-species crossover are used to improve the search ability. The results of several benchmark problems show that this algorithm is quite effective at the optimization of multi-peak functions by finding all peaks within the landscape.