Two Sub-swarms Quantum-Behaved Particle Swarm Optimization Algorithm Based on Exchange Strategy

In this paper, a Two Sub-swarms Quantum-behaved Particle Swarm Optimization Algorithm Based on Exchange Strategy (TS-QPSO) is proposed. Two sub-swarms of particles with quantum Behavior are set up in TS-QPSO. Once the whole swarm falls into local optima and the best value of the global swarm is not improved after the allowable iterations, the exchange strategy will be carried out. The amount of exchange particles is different in each searching phase. In this way, the population diversity can be improved greatly and the problem that falling into local optima can be avoided effectively. Experiment results show that the overall performance of TS-QPSO is superior to QPSO algorithm and TSPSO algorithm.