Paper Title
FORESIGHTED MEDICAL RESOURCES ALLOCATION DURING AN EPIDEMIC OUTBREAK

Abstract
Abstract - Although some reports suggest that current medical resource allocation during epidemic outbreaks is short-sighted, others argue that a future-focused approach may lead to a better balance of supply and demand. To explore this idea, we created a model for foresighted medical resource allocation to assist governments in managing large-scale epidemics. Our model includes a demand forecasting function that takes into account the last-period demands, unfulfilled demand from the previous period, and uncertain demand. The government then uses this information to make current-period allocations based on the expected demand until the end of the planning horizon. Our findings indicate that the optimal allocation is dependent on the allocation capacity for each period and that foresighted allocation is always higher than one-period allocation but decreases as allocation capacity increases. Additionally, if oversupply costs are negligible, both models' optimal allocations are equivalent to the allocation capacity. Our research provides valuable insights for governments looking to allocate medical resources effectively during an epidemic outbreak. Keywords - Health Care; Emergency Logistics; Stochastic Dynamic Programming