Abstract: In view of the shortcomings of artificial bee colony algorithms,such as the low convergence rate and being trapped into local optimums owing to choosing the food source based on direct mapping probability,and low optimization precision,a chaotic artificial bee colony optimization algorithm based on rank mapping probability (CABC-R) was proposed in this paper．The proposed search process was divided into two different phases:in the first one an ABC global optimizer based on rank mapping probability was created to get a global solution,in the second one the local chaotic optimization algorithm was gotten to obtain more precise an optimum．The simulation results on 10standard test complicated functions indicate that the proposed optimization algorithm is rapid and effective,and that it outperforms the current global optimization algorithms such as ABC,JADE,MSEP and RABC.

Key words: Optimization method,Artificial bee colony algorithm (ABC),Chaotic optimization algorithm (COA),Rank mapping probability,Direct mapping probability