Joint optimization of maintenance and speed selection for transportation systems

There is an increasing demand for long-distance emergency transportation missions. Transportation systems often perform missions in harsh environments, and the valid shock probability varies when the system is shocked at different speed levels. System failure or excessively long transportation times can cause significant economic losses, so both successful completion and the shortest possible time are critical for emergency missions. Based on the above insights, this paper investigates the joint optimization of maintenance and speed selection for transportation systems in stochastic shock environments. The optimization goal is to minimize the total cost of system failure, maintenance, and operation, aiming to complete transportation missions with high reliability and in a short time. A Markov decision process is formulated to model the system operation process and obtain the optimal joint policy. For comparison, two heuristic policies are proposed. The effectiveness of the joint optimization policy to reduce the cost is verified by taking the UAV to perform an emergency mission as an example. The results show that under certain circumstances, the system has the opportunity to adjust its speed to control the risk of system failure.