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The Artificial Bee Colony (ABC) algorithm is a new swarm optimization algorithm with good numerical functions optimization results. In order to enhance the performance ability of ABC algorithm, a hybrid ABC (HAB) algorithm is presented where swarming behavior of bacterial foraging optimization algorithm is introduced into the ABC algorithm to do local search. The performance of the proposed method is examined on well-known six numerical benchmark functions and the obtained results are compared with basic ABC algorithm and BFO algorithm. The experimental results show that the proposed approach is very effective method for solving numeric benchmark functions and successful in terms of solution quality and convergence to the global optimum, especially on the multimodal functions.

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