Artificial Bee Colony Algorithm Based on Adaptive Cauchy Mutation

For the problem of the standard artificial bee colony such as falling into local optimum, this paper proposes an adaptive Cauchy mutation artificial bee colony (ACMABC). The algorithm introduces an adaptive factor which can expand the search of the swarm and uses the Cauchy distribution to improve the universality of colony search. Finally, the ACMABC use to do simulation experiment. The experiment results show that this algorithm not only can prevent falling into local optimum effectively, but also has higher accuracy.