Artificial bee colony algorithm based on self-adaptive greedy strategy
Zeyu Yang, Hao Gao, Haidong Hu · 2018
Artificial bee colony algorithm is an effective optimization algorithm. In this paper, a novel artificial bee colony algorithm is developed based on a self-adaptive greedy strategy (SAGABC). Each bee should select whether adopts greedy strategy or not based on its fitness value on each generation. Individuals with worse fitness value update with non-greedy strategy then they have more opportunity to get a better score while individuals with better fitness value update with greedy strategy to speed up convergence. In other word, non-greedy part improves diversity of population which contributes to a better global searching ability. Finally, the experience results demonstrate that the developed method shows a competitive performance compared with traditional ABC and other optimization algorithms on a number of benchmark functions.