Bacterial foraging algorithm based on gradient particle swarm optimization algorithm
基于梯度粒子群算法的细菌觅食算法

To overcome the drawbacks of bacterial foraging algorithm for the optimization process, that the weak ability to perceive the environment and vulnerable to perception of local extreme. This article will merge the idea of GPSO algorithm into the bacterial foraging to improve the speed and convergence capabilities of BFA and according, this paper presented a bacterial foraging algorithm based on gradient particle swarm optimization GPSO-BFA. 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 4 kinds of bacterial foraging algorithm.