Abstract
This is a new semi-distributed differential evolution algorithm with best determination method and species evolution (DESBS). This algorithm is based on fact- evolution of species around niche. In DESBS, the best determination method determines the best individuals of population. These best individuals act as niches and the species are evolved around these best individuals. Over the period of time, each species evolved separately, using standard differential evolution algorithm. The evolving efficiency of each species evaluated separately and inefficient species are merge to nearby species. The scale-up study is performed to find out best parameter setting and the results are compared with other state-of-art algorithms like CoDE, EPSDE and standard differential evolution algorithm. The results show that the DESBS perform better than SDE in multimodal functions and CoDE, EPSDE in rotating optimization function
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