Improved Particle Swarm Optimization for Constrained Optimization

Abstract

In this paper, we present an improved particle swarm optimization (PSO) algoritlim to solve constrained optimization problems. The proposed approach, called MPSO, employs a novel mutation operator to enhance the global search ability of PSO. In order to deal with constrains, MPSO uses mean violations mechanism and boundaries search. Simulation results on five famous benchmark problems show that MPSO achieves better results than standard PSO and another variant of PSO.