In order to allocate the limited Freeway Service Patrols (FSP) resources reasonably, the optimization model of the deterministic FSP routing and scheduling was established. the problem of deploying the limited FSP resource was investigated, the objective of the optimization modeling based on the full coverage model was minimizing the overall average incident response time; the connected routing was treated as a chromosome, the improved algorithm combined genetic with Simulated Annealing was coded based on MATLAB, dynamic crossover and mutation probability and the Metropolis criterion for simulated annealing was added to the progeny update, moreover, the dynamic genetic algorithm was used to vehicle scheduling in the improved algorithm; the improved algorithm was validated based on Sioux Falls" network and data, and the calculated results were compared with the corresponding scenario and simulated annealing algorithm. The results show that the results were reduced by 23.35% and 28.28% compared the improved algorithm with the corresponding scenario, moreover, a comparison with the simulated annealing algorithm shows that the improved algorithm performs better in searching for the optimal solution and computational efficiency, and it is more suitable for medium and large road network in Routing and Scheduling Optimization.