Analysis of Adaptive Mutation in Crazy Particle Swarm Optimization

This paper contributes an investigation in the utilization of adaptive mutation in a very prominent edition of particle swarm optimization technique i.e, crazy particle swarm optimization for the betterment of finding out the global best solution. In the field of swarm intelligence, particle swarm optimization is recognized as one of the popular techniques, which have shown an accepted performance in various real world engineering problems. Simultaneously, it has some cons which inspire the researchers for further modifications to get a better output with the improvement of its convergence quality. Here we proposed one enhanced version of Crazy PSO i.e. Adaptive mutated Crazy PSO. After the results of simulating experiment, it has been observed that Adaptive mutated Crazy PSO has exhibited improved results as compared to the basic Crazy PSO. The addition of Adaptive mutation helps in the achievement of better performance in Crazy PSO which has been tested on various benchmark functions