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,an Artificial Bee Colony optimization algorithm based on Hybrid rank mapping probability and Chaotic search (ABC-HC) was proposed in this paper．First,two computing probability method to choose food sources were created based on rank mapping.Then the ABC algorithm based on combining the two probability methods in a onlooker bee phrase was proposed in order to keep diversities of the solutions and not to be trapped into local optimums.Finally,in a scout bee phrase,random search was replaced with chaotic search to get a higher convergence rate and a global solution effectively．The simulation results on 10standard test complicated functions indicate that the proposed optimization algorithm is rapid and effective and outperforms the standard ABC algorithm and the evolutionary ones.

Key words: Artificial bee colony algorithm (ABC),Rank mapping probability,Direct mapping probability,Chaotic search,Random search