Research on TSP Solution Based on Improved Simulated Annealing Algorithm

Anzhi Qi
2018 Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)   unpublished
Travelling Salesman Problem (TSP) is a typical combinatorial optimization problem. The main idea of the problem is that given a number of cities and the distances between each city and tries to get the shortest path that visits each city exactly once and back to the starting point. This report introduces multiple arithmetic operators to improve the simulated annealing algorithm to apply in the solution of TSP. The result shows that the improved simulated annealing algorithm is effective and
more » ... cient. Simulated Annealing Algorithm and Its Improvement Simulated Annealing. The simulated annealing algorithm (Simulated Annealing) was first seen in IBM Thomas.J. Watson research center in the article by S.Kirkpatrick et al, they studied the optimization of the portfolio, according to the iterative improvement proposed simulated annealing algorithm, simulated annealing algorithm has strong local search ability. The simulated annealing algorithm is derived from the principle of solid annealing, which heats the solid to a sufficiently high level, and then cools it down slowly to achieve the lowest energy point. Conversely, if the rapid cooling, it cannot reach the lowest point. During heating, temperature rise inside the solid particles with the shape into disorder, can be increased, and the slow cooling when the particle is orderly, temperature has reached equilibrium in each state, and finally reached the ground state at room temperature can be reduced to a minimum. According to the Metropolis criterion, the probability that the particle tends to equilibrium at the temperature T is exp (-E/ (kT)), where E is the internal energy at the temperature T, E is the change, and K is the Boltzman constant.
doi:10.2991/macmc-17.2018.27 fatcat:t7lofq7amvbitam2tcol3zjswi