부산대학교 도서관

Particle Swarm Optimization (PSO) algorithm is a new swarmed intelligent optimization technique, which has been widely used to solve various and complex optimization problems, but there are still premature, low precision, slow convergence phenomenon. We proposed an improved PSO based on update strategy of double extreme value by analyzing the updating ways of double extreme. Improved algorithm has good global searching capability through the classical test function, the new algorithm has solutions of high precision, fast convergence, and it is proved that the new algorithm is feasible and effective.