Research on global artificial bee colony algorithm based on crossover

Abstract

In order to overcome the shortcomings of artificial bee colony algorithm induding slow convergence speed, easily falling into local optimum value, neglect of development and other issues, Mechanism of other bionic intelligent optimization algorithms, A new algorithm of Global Artificial Bee Colony algorithm based on crossover which can effectively improve the convergence rate, enhance the development of the algorithm and the global optimization ability is proposed, and the algorithm can effectively avoid the local optimum. Finally, the Seven standard test functions are selected to carry out the experiment and simulation. The results show that the convergence speed and accuracy of the proposed algorithm (CGABC) are significantly improved compared with other algorithms such as ABC algorithm, GABC algorithm and so on.