This paper represents a hybrid algorithm for travelling salesman problem. The main idea of the hybrid algorithm is to harness the strong global search ability of the genetic algorithm and the high local search capability of the simulated annealing algorithm. The real distance between customers has been used on the basis of GIS in order to make the result more suitable to be used in real-life. The algorithm has been tested on standard examples and it showed that the algorithm proposed in this paper has improved the results.
Travelling salesman problem Genetic-simulated annealing algorithm Geographical information system
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This research is supported by the National Natural Science Foundation of China (71172168, 71241025), the fundamental Research Founds for the Central Universities (FRFSD13–003D, FRFSD130304)
Agarwal Y, Mathur K, Salkin H (1989) A set-partitioning based exact algorithm for the vehicle routing problem. Networks 19(7):731–739CrossRefGoogle Scholar
Badeau P, Guertin F, Gendreau M, Potvin JY, Taillard E (1997) Parallel tabu search heuristic for the vehicle routing problem with time windows. Transp Res C-Emerg 5(2):109–122CrossRefGoogle Scholar
Balinski M, Quandt R (1964) On an integer program for a delivery problem. Oper Res 12(2):300–304CrossRefGoogle Scholar
Christofides N, Mingozzi A, Toth P (1981) Exact algorithms for the vehicle routing problem based on spanning tree and shortest path relaxations. Math Program 20(1):255–282CrossRefGoogle Scholar
Clarke G, Wright JW (1964) Scheduling of vehicles from a central depot to a number of delivery points. Oper Res 12(4):568–581CrossRefGoogle Scholar