Particle Swarm Optimization Using Sobol Mutation

In this paper, we present a new mutation operator called the systematic mutation (SM) operator for enhancing the performance of basic particle swarm optimization (BPSO) algorithm. The SM operator unlike most of its contemporary mutation operators do not use the random probability distribution for perturbing the swarm population, but uses a quasi random Sobol sequence to find new solution vectors in the search domain. The comparison of SM-PSO is made with BPSO and some other variants of PSO. The empirical results show that SM operator significantly improves the performance of PSO.