Abstract:

Considering the premature convergence problem of Fruit Fly Optimization Algorithm (FOA), a new adaptive fruit fly optimization algorithm based on bacterial migration (AFOABM) is proposed. During the running time, according to the evolutionary stagnation step size, bacterial migration is adaptively introduced into FOA to improve its ability of jumping out of the local extreme; and according to the fitness values, each individual is assigned different adaptive migration probability in order to avoid the problem of possible solutions degradation resulting from migration. Experimental results show that the new algorithm has the advantages of better global searching ability, speeder convergence and more precise convergence.

Key words: bacterial foraging, bacterial migration, fruit fly optimization algorithm, adaptive