Using particle swarm optimization to solve test functions problems

In this paper the benchmarking functions are used to evaluate and check particle swarm optimization (PSO) algorithm. However, utilized have two dimension but they selected with different difficulty models. order prove capability of PSO, it is compared genetic algorithm (GA). Hence, algorithms in terms objective standard deviation. Different runs been taken get convincing results parameters chosen properly where Matlab software used. Where suggested can solve engineering problems outperform others term accuracy speed convergence.