The Improved Artificial Bee Colony Method and Its Application on UAV Disaster Rescue

An improved Artificial Bee Colony (ABC) algorithm is proposed in this paper. In contrast to the traditional method, which may drop into the local optimization and meet the slow convergence problem, a global population optimization-based method is developed. The equilibrium searching factors are designed to speed up the convergence effect and expand the searching ability. To evaluate the effectiveness of proposed method, on one hand the algorithm computation effect is assessed. The convergence effect of fitness value can be improved. The experiment results show that the proposed method is better than the ordinary ABC algorithm. On the other hand, an optimal path planning mission of the UAV disaster rescue is also compared between the traditional ABC and our proposed methods. The results also illustrate that our proposed method has a better performance to avoid the threaten sources on ground.