Objective: This study proposes an optimization-based mathematical model for establishing a rational operational strategy for Deployable Medical Systems (DEPMEDS) under limited resources and time constraints. Method: The study applied a Mixed-Integer Linear Programming (MILP) approach, an optimization technique designed to determine the optimal combination of available resources. MILP was employed to maximize the expected number of timely evacuees by considering constraints such as the limited time for patient arrival, evacuation distance, vehicle speed, and transportation capacity. Realistic casualty scenarios were simulated using MILP, implemented in the open-source R programming environment. Results : Simulation results showed that DEPMEDS deployment was most efficient at evacuation distances of 10km or less, when a sharp efficiency decline beyond 14.5km. These results highlight the importance of considering both time and distance constraints when planning medical operations and provide quantitative grounds for asset allocation and optimal deployment range determination. Conclusion : This study demonstrates that a scientifically grounded operational strategy for DEPMEDS can be established by incorporating battlefield conditions and available resources. It also highlights the potential for future development into a real-time, AI-based decision-support model for future battlefield medical planning.