Coal mine locomotive transportation plays the role of transporting materials and gangue in the daily production of coal mine. As the carrier of transportation, whether the locomotive can safely and efficiently complete the transportation task assigned by the dispatching center is undoubtedly very important for coal mine production. Reasonable scheduling optimization of locomotives can not only improve the transportation efficiency, but also greatly reduce the collision and other safety accidents. In this paper, an improved optimization algorithm combined with cross factor and simulated annealing algorithm is used to solve the scheduling optimization problem of underground locomotive transportation in coal mine. The improved algorithm introduces cross factor to update the individual position, and selects the individual to enter the next iteration according to the fitness increment of simulated annealing algorithm. In this way, the parameters of optimization algorithm are easy to adjust and the information sharing process is retained. It also solves the problem of premature and low precision of Drosophila algorithm. Through the simulation of underground locomotive transportation in coal mine, it is proved that the path planned by the algorithm is more reasonable and the efficiency of locomotive transportation is higher.