Abstract:

Particle swarm optimization algorithm is a heuristic global optimization technique based on swarm intelligence. Each particle of the swarm represents  one candidate solution of the problem being optimized. The algorithm finds optimal regions of complex problem spaces through the pheromone interaction o f particles. This paper reviews the basic theory, and describes the seeking procedure of the personal best and the global best in PSO through establishing memory table. At the same time, this paper also presents some kinds of improved versions of PSO and research situation, and also gives the future res  earch directions.

Key words: particle swarm optimization, swarm intelligence, heuristic, memory table