Abstract

A new differential evolutionary algorithm with species and best vector selection (DESBS) has been proposed. It uses best determination method (BDM) to determine the best members in population. Each best member is considered as a niche in population. The species formation takes place around these niches. Once the species get formed then the standard differential evolution algorithm (SDE) has been used. If species is not performing well, then the merging to the nearby species takes place. The scale up study of various parameters of DESBS is done to get best parameter setting. The performance of newly proposed algorithm is tested on uni-modal and multi-modal test functions. It got success in solving wide range of problems. The results are compared with standard Differential evolution algorithm (SDE) and other state-of-art algorithms. The results are encouraging one.

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