A Novel Binary Particle Swarm Optimization Method Using Artificial Immune System

Particle swarm optimization, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real value optimization problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new binary particle swarm optimization method based on the theory of immunity in biology is proposed. In spite of the simplicity of the technique, simulation results show the improvement of the searching ability and increment in the convergence speed in comparison with the other binary PSO and genetic algorithm