Optimal Routing in Traveling Salesman Problem using
Artificial Bee Colony and Simulated Annealing
Mohammad Shokouhifar, Ali Jalali, Hamid Torfehnejad
Department of Electrical and Computer Engineering, Shahid Beheshti University, G.C.,
Tehran, Iran
m_shokouhifar@sbu.ac.ir, a_jalali@sbu.ac.ir, h_torfehnejad@sbu.ac.ir
Abstract:
Traveling salesman problem (TSP) is a popular routing problem, which is a sub-problem of many application domains
such as transportation, network communication and vehicle routing. TSP belongs to the class of NP-hard problems.
Among many approaches which have been proposed for TSP, evolutionary and swarm intelligence algorithms efficiently
applied to solve it, and attempt to avoid trapping in local minima. In this paper, a hybrid algorithm based on Artificial
Bee Colony (ABC) and Simulated Annealing (SA) is proposed for TSP. The proposed algorithm, named ABCSA, is
divided into two phases. The first phase searches globally the search space via population-based ABC algorithm. The
second phase applies local-based SA algorithm in order to improve the final solution of ABC. Instead of a random
solution, the final best solution gathered by ABC is considered as the initial solution of SA. To demonstrate the
effectiveness and efficiency of the proposed algorithm, some benchmark problems from TSPLIB were tested and
compared with the techniques of GA, PSO, SA and ABC. Results show that our algorithm achieved shorter distances in
all cases with fewer generations and running time.
Keywords: traveling salesman problem, routing, neighborhood search, artificial bee colony, simulated annealing.