Artificial Bee Colony Algorithm with Crossover Strategies for Global Numerical Optimization

In this paper, a new variant of artificial bee colony (ABC) algorithm is proposed for solving numerical optimization problems. In order to increase population's solution searching ability, the crossover operation of genetic algorithm (GA) is involved to produce new potential offspring. In the experiment, the CEC 2005 test functions are adopted for test proposed method and compared it to related works. From the results, it can be observed that the proposed method performed better performance than two variants of ABC approaches.