Bacterial foraging algorithm based on gradient particle swarm optimization algorithm

To overcome the drawbacks of bacterial foraging algorithm for the optimization process,that is the weak ability to perceive the environment and vulnerable to perception of local extreme. This article will merge the idea of gradient particle swarm optimization algorithm into the bacterial foraging to improve the speed and convergence capabilities of BFA and according to this a bacterial foraging algorithm based on GPSO (GPSO-BFA) is presented. The presented hybrid method incorporates the advantages of the excellent global searching of the BFA and the local speedy convergence of the gradient method. Simulation results on six benchmark functions show that the proposed algorithm is superior to the other four kinds of bacterial foraging algorithm.