Research on function optimization problem based on artificial bee colony algorithm

Abstract

Artificial bee colony (ABC) algorithm is a kind of artificial colony algorithm simulating the behavior of bees swarm intelligence optimization algorithm. Because it has less control parameters, easy to implement, the advantages of simple calculation, has been more and more researchers focus on. But the basic artificial colony algorithm still has the shortcomings, such as premature convergence, easy to fall into local optimum and evolution, such as the late slower convergence shortcomings. In view of the ABC algorithm search equation of the shortcoming of weak local searching ability of the variation equation by differential evolution algorithm and evolution equation of particle swarm optimization (PSO) algorithm, puts forward two kinds of artificial colony algorithm based on improved search equation, respectively is the artificial colony algorithm based on the optimal solution to guide and mixed artificial colony algorithm, experimental simulation show that the improved algorithm in the optimal solution and precision of algorithm convergence ability has a certain degree of improvement or enhancement.