An improved cooperative PSO algorithm

Traditional PSO algorithms suffer form the “curse of dimensionality”, which implies that their performance deteriorates as the dimensionality of the search space increase. This paper presents a variation on the traditional PSO algorithms, called improved cooperative particle swarm optimization, or COPSO, employing cooperative behavior to significantly improve the performance of the original algorithms. Firstly, traditional PSO algorithms were used to update the position and velocity vectors of particles, and then a reference global best position was obtained by using cooperative operator on the best positions of particles encountered so far. Such reference global best position was used to update the current global best position of the swarm, which was calculated by above traditional PSO algorithms. Application of the COPSO algorithm on there benchmark optimization problems showed a marked improvement in convergence rate over some traditional PSO algorithms.