Particle Swarm Optimization with Crossover Operator for Global Optimization Problems

Abstract

We propose a modified particle swarm optimization (PSO) algorithm named SPSO for the global optimization problems. In SPSO, we introduce the crossover operator in order to increase the diversity of the swarm. The crossover operator is contracted by forming a simplex. The crossover operator is used if the diversity of the swarm is below a threshold (denoted h low ) and continues until the diversity reaches the required value (h high ). The six test problems are used for numerical study. Numerical results indicate that the proposed algorithm is better than some existing PSO.