Research on Civil Aviation Cargo Transport Route Planning Based on Improved SA Algorithm

Artificial intelligence and intelligent algorithms have shown great potential in solving complex optimisation problems, especially in the path optimisation problem in the field of transportation. Aiming at the route planning problem in civil aviation cargo transport, the study proposes an optimisation model with the improved simulated annealing algorithm. The model firstly establishes a transport path model based on time window, and then, it is combined with genetic algorithm. Simulated annealing algorithm and genetic algorithm are introduced as comparative models, and the experimental results show that the optimal distance similarity rates of genetic algorithm model, simulated annealing algorithm model, and improved simulated annealing algorithm model are 89.2%, 96.4%, and 99.5%, and the processing times are 0.35s, 0.28s, and 0.15s, when the number of iterations is 500.The research results show that the improved hybrid algorithm based on simulated annealing can effectively optimize the accuracy of civil aviation cargo transport route planning, which provides efficacious assistance with regard to decision-making in the context of actual transport.