Online bipartite matching methodology for anti-epidemic resources allocation: an adaptive time window based on reinforcement learning

The results revealed that, although the average matching rate consistently increases, the average waiting time initially decreases before rising again as the matching time window expands. This finding implies that health operations managers should modify the matching time window in response to changing epidemic dynamics and resource availability.