Static learning particle swarm optimization with enhanced exploration and exploitation using adaptive swarm size

In this paper, a novel Static Learning (SL) strategy to adaptively vary swarm size has been proposed and integrated with Particle Swarm Optimization algorithm. Besides, the whole population has been divided into two sub swarms, where particles of different sub swarms interact within their neighbourhood and the existence of better particle is determined by evaluating its survival probability. Proper resource based particle replacement scheme and...