Quantum-behaved particle swarm optimization with generalized local search operator for global optimization

In this paper, we propose a local quantum-behaved particle swarm optimization (LQPSO) as a generalized local search operator. The LQPSO is incorporated into a main quantum-behaved particle swarm optimization (QPSO), which leads to a hybrid QPSO scheme QPSO-LQPSO, with enhanced searching qualities. The main QPSO performs global exploration search while the LQSPO exploits a neighborhood of the current solution provided by the main QPSO to search better solutions. The proposed QPSO-LQPSO scheme is tested on a test set. Simulation results demonstrate the efficiency of the proposed QPSO-LQPSO scheme. For the same number of fitness evaluations, QPSO-LQPSO exhibited a significantly better performance than other particle swarm optimization algorithms.