Solving TPS by SA Based on Probabilistic Double Crossover Operator

The Traveling Salesman Problem (TSP), the study of its heuristic algorithm and approximate algorithm has always been a hot research direction. In this paper, we propose a simulated annealing algorithm based on the probability double crossover operator, dynamically combine the Swap operator and the Inversion order operator. In each annealing process Compared with the previous single operator, our algorithm can select different crossover operators based on probability to generate new feasible solutions, and the algorithm is more sensitive to the variability of feasible solutions. The beilin52 example shows: Compared with the classic simulated annealing algorithm based on the exchange operator, our algorithm increases the variability of the feasible solution of the TSP problem in the optimization iteration process, making the current optimal solution easier to jump out of the local optimal solution “Trap”, so as to better converge to the global optimal solution.