Solution of global optimization problem using mutation operator with hybrid PSO algorithm

While searching for a local optimum with Classical Particle Swarm Optimization algorithm, all the particles in the swarm come towards the local optimal point and gather around it. So it becomes very difficult to escape from this state. To avoid such premature convergence we present a new algorithm called MPSO (Mutated Particle Swarm Optimization) that uses a new way of generating the mutated swarm particles. The proposed algorithm is validated on three standard benchmark functions.