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In this document, it will be introduced the pro­posal for optimization algorithm based on particle swarms vorticity features, where a search group is considered through the association to the midpoint of the swarm and an individual search is given for the best position of each individual. The search group seeks to achieve the convergence of the whole swarm, whereas the individual search allows better exploration in pursuant of space. The algorithm has convergence and exploration behavior given by the selected model which is based on the behavior of a swarm of individuals. For establishing the algorithm performance, a set of test functions in two dimensions is used.

Algoritmo de optimización basado en enjambres de partículas con comportamiento de vorticidad y búsqueda individual y grupal