The Particle Swarm Optimization (PSO) is a new global optimization method based on a metaphor of social interaction. In this paper, a new version of particle swarm optimization algorithms has been proposed. This algorithm has been developed by combining two different approaches of PSO i.e., Standard Particle Swarm Optimization (SPSO) and Mean Particle Swarm Optimization (MPSO). Numerical experiments for several scalable and non-scalable problems have been done. The results indicate that the proposed algorithm performs better than the existing ones in terms of efficiency, reliability, accuracy and stability.