Traveling Salesman Problem（TSP）is a typical NP-hard problem in combinatorial optimization field,the solution time of which appears exponential growth along with problem optimization algorithms have been unable to meet their needs, and it has become a heat subject in recent years that TSP is solved by the way based on intelligent algorithms. Simulated annealing algorithm is a random iterative optimization algorithm which combines the physical annealing process and combinatorial optimization together , and it can convergence to the overall optimal solutions by Metropolis criteria. Using simulated annealing algorithm to solve the TSP problem is an ideal method. This project uses simulated annealing algorithm to solve TSP problem. According to TSP problem and the characteristics of simulated annealing algorithm, it designs on the positions and algorithm rules of cities. It also constructs a basic window based on C++ and defines random city positions in the window. At the same time, the project plans for neighborhood search methods and calculation of path difference, which speed up algorithms. The experimental test result shows that the project has been applied successfully.
牙签victor
