Discrete artificial bee colony algorithm with fixed neighborhood search for traveling salesman problem

For the artificial bee colony algorithm (ABC), it is easy to fall into local optimum and has lower convergence accuracy when solving the traveling salesman problem. For addressing this demerit further, a discrete artificial bee colony algorithm with fixed neighborhood search for traveling salesman problem (TSP), called DABC-FNS, is proposed. In DABC-FNS, the solution obtained by the discrete artificial bee colony algorithm is expressed by positive integer coding method. Meanwhile, the local enhancement strategy and the 2-opt strategy with fixed neighborhood search are introduced to improve the solution accuracy of the ABC algorithm. In order to verify the effectiveness of the DABC-FNS algorithm, more than 30 benchmark TSP instances are simulated by DABC-FNS algorithm and other state-of -the-art competitors. The experimental results show that the DABC-FNS algorithm has achieved better accuracy for most TSP instances, which also demonstrates that it can overcome the premature phenomenon and has certain advantages in solving the traveling salesman problem.