Modifications of particle swarm optimization for global optimization

Particle swarm optimization (PSO) is one of the most famous nature-inspired algorithms, which has shown good performance on many optimization problems. To enhance the performance of PSO, this paper presents some modifications of PSO. The proposed approach is called MPSO, which employs a novel local search technique to obtain better candidate solutions. In order to verify the performance of the MPSO, we test it on ten well-known benchmark functions. Experimental results show that MPSO achieves better results than standard PSO and another improved PSO variant on the majority of test functions.