An enhanced bacterial foraging optimization with adaptive elimination-dispersal probability and PSO strategy

Bacterial Foraging Optimization(BFO) is a comparatively new optimization algorithm which learn from the foraging behavior of bacteria. The elimination and dispersal step is the major step of BFO to get the global search ability. An Enhanced Bacterial Foraging Algorithm (EBFO) is presented in this paper, which is a variation of the original BFO algorithm. This new algorithm uses an adaptive elimination-dispersal probability according to bacterial fitness, meanwhile it carry out an Particle Swarm Optimization (PSO) operator just after the swim step. From the result of experiment on 6 benchmark functions, we can draw the following conclusions that the new algorithm has the advantages of better global searching ability, speeder convergence and more precise convergence.