A novel artificial bee colony algorithm for numerical function optimization

Abstract

Artificial Bee Colony (ABC) algorithm is a widely used optimization algorithm. However, it is good in exploration but poor in exploitation. To improve the optimization performance of ABC algorithm, two novel search mechanisms served as the search equations are proposed. Firstly, the improved algorithm integrates the information of previous best solution into the search equation in the onlookers to improve the exploitation. Secondly, the search policy of the scouts is modified, the distance between the optimal and the worst solutions is utilized to replace the worst solution, so as to avoid producing worse solution. The result shows that the proposed algorithm has higher precision and stability compared with other algorithms.