Particle Swarm Optimization Algorithm for Solving Optimization Problems

Many optimization techniques used in solving optimization problems has been developed by inspiring from the events in nature. Particle Swarm Optimization (PSO) algorithm is a population based optimization technique inspired by social behavior of bird flocking and fish schooling. In this paper, PSO is compared with Genetic Algorithms and Differential Evolution Algorithm by using test functions. The results show that the PSO, in most problems, is able to find much better solutions and better convergence compared to other two algorithms.