Artificial Bee Colony Based on Adaptive Selection Probability

Abstract

Because of the powerful searching ability of artificial bee colony algorithm, it has applications in various fields. However, it still has a drawback on local search ability. Therefore, an adaptive selection probability ABC algorithm (called PABC) is proposed to improve its local search ability. In the multi-strategy search solutions, a probability is assigned to each strategy and the probability is adaptive adjusted to control the choice of strategy. Meanwhile, a modified mean center is introduced to replace the global best solution to guide search. The proposed PABC is proved to have better optimization ability than some other improved ABCs by testing classical 12 functions.