An Improved Artificial Bee Colony with Self-Adaptive Strategies and Application

Artificial bee colony algorithm (ABC) has been becoming a hot topic of swarm intelligence. Artificial bee colony algorithm shows great advantages in solving path problems. There still exist some shortcomings in basic ABC algorithm, such as low convergence rate and easily falling into local optimization. Hence, an improved Artificial Bee Colony algorithm is proposed in this paper. In the improved Artificial Bee Colony, self-adaptive strategies for updating food source is introduced to ensure time and accuracy of algorithm. The proposed algorithm is also applied to the traveling salesman problem. Experiments show the effectiveness of improved algorithm.