Adaptative particle swarm optimization algorithm with non-iterative electrostatic repulsion and social neighborhood Algoritmo de optimización por enjambre de partículas adaptativo con repulsión electrostática no iterativa y vecindad social

Bio-inspired algorithms are algorithms inspired in the nature commonly used for solving optimization problems. A class of the bioinspired optimization algorithms is swarm algorithms which mimic the collective behavior in animals. An example is Particle Swarm Optimization (PSO) based in the social behavior of bird flocking. This paper presents a variation on the basic PSO algorithm, called A2PSO. The A2PSO has two important characteristics: non-iterative electrostatic repulsion and social neighborhood. The goal is to improve the location and interaction of the particles. Experiments were realized on benchmark test functions with unimodal and multimodal functions. The A2PSO achieves good results in solving benchmark test functions as compared to other recent important works on PSO.