A Self-Adaptive Hybrid Algorithm of PSO and BFGS Method

This paper presents a novel particle swarm optimization (PSO) algorithm to enhance the performance of PSO. The proposed approach, called self-adaptive hybrid PSO (SHPSO), employs a self-adaptive inertial weight factor to lead the search direction of the population and generate good candidate solutions, next uses BFGS method to improve the local search ability of the algorithm. In order to verify the performance of SHPSO, we test it on six well-known benchmark functions. The simulation results show that SHPSO achieves better results than standard PSO and LPSO in all test cases.