Fast parameter free Smart particle swarm optimization (SPSO)

The qualitative value of an optimization technique depends upon the way it explores and exploits the search region. The proposed Smart PSO (SPSO) is a new version of PSO that uses the swarm particles smart behavior in the search space to solve global optimization problems. Unlike the traditional PSO algorithm, SPSO does not depends upon the initial velocities of the particles during successive iteration. It converges the particle towards global optima using cognitive and social knowledge only. This personal environment and social information gives the algorithm a fast capability of exploitation and exploration This fact has been supported by empirical simulation of seven standard benchmark functions and the comparative results clearly evident that SPSO is better than DIW-PSO, Rand-PSO and QPSO.