In order to form a scientific and reasonable highway network layout and provide theoretical support for the practice of highway network planning, based on the importance degree of the nodes and certain constraints, a mixed integer programming model was constructed to meet the transportation demand between nodes. The goal of the planning model was to minimize the total travel time of the highway network. On this basis, a two-stage heuristic algorithm based on random walk algorithm and simulated annealing algorithm was designed. The random examples generated by MATLAB were solved, taking the importance degree of road section and transportation demand as heuristic conditions. The results showed that at the beginning of the algorithm iteration, the nodes with higher node importance were connected first. With the increasing number of iterations and certain random interference, the nodes were achieved full connectivity and continuously optimized with the objective of minimizing the total travel time. Finally, the highway network layout scheme with the optimal objective function value was obtained. The solution process of the example conforms to the practice law of highway network planning, which shows the effectiveness of the model and the algorithm. At the same time, it shows that the simulated annealing algorithm has a certain optimization effect on the initial solution of the random walk algorithm. It can be seen that the two-stage heuristic algorithm can solve the NP-hard problem in a short time and obtain a relatively satisfactory solution, which can provide a certain method reference for solving large-scale network optimization problems.
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