A new method used for traveling salesman problem based on discrete Artificial Bee Colony algorithm

Abstract

We propose a new method based on discrete Artificial Bee Colony algorithm (DABC) for traveling salesman problem. We redefine the searching strategy and transforming mechanism of leading bees, following bees and scout bees according to discrete variables. The transition of swarm role is based on ratios factor of definition. Leading bees use 2-Opt operator and learning operator to accelerate the convergence speed and to search the neighborhood. The searching of following bees introduces tabu table to improve the local refinement ability of the algorithm. Scouts bees define an exclusive operation to maintain the diversity of population, so it is better to balance the exploration and exploitation ability of the algorithm. Finally, the experimental results show that the new algorithm can find relatively satisfactory solution in a short time, and improve the efficiency of solving the traveling salesman problem.