地震或颱風是台灣常面對的自然災害，經常使台灣遭受嚴重的傷亡或財物損失。當災害導致短時間內出現大量傷患時，災區周遭醫院出會現大量的醫療資源需求，此時須從外地調配醫療資源支援需求點，而災害也會使部分道路損毀或中斷而失去原有功能，提高災後運送醫療物資至災區的時間與難度。若未能在有效時間內滿足醫療資源需求，將會造成大量傷亡。在災前將部份資源超前部署至各醫院是個減少災害傷亡的好方法。本研究考量不同的災害情境下的醫療資源需求量與災後道路損毀，探討在災前需部署多少醫療資源到各醫院，以最小化災害造成的影響。針對災後的高度不確定性，本研究提出一個兩階段隨機規劃 (two-stage stochastic programming)模型。並透過模擬災後情境，評估各地區災後的醫療資源需求與路網狀況，最終找出災前醫療資源的最佳部署方式。協助決策者進行備災政策，提高台灣的防災能力。

When disasters happen, a large number of patients would occur in a short period of time, and cause a lot of demand of medical resources in local hospital. At this time, medical resources have to be delivered to every demand point. Disasters also damage some roads, and increase the time and difficulty of delivering medical resources to the disaster area after the disaster. If the decision maker can’t meet the demand of medical resources within the effective time, there would be a large number of casualties. Preemptive allocating medical resource to some hospitals in advance is a good way to reduce the impact of disasters. This study considers different disaster scenarios, and explores how much medical resources should be preemptive allocated to each hospital before disasters happened to minimize the impact of the disaster. In order to deal with the uncertainty after the disaster, this study proposes a two-stage stochastic programming model. The proposed model evaluates the demand and network condition after disasters happened by simulation and finally get the optimal allocation. The model can also help decision-makers in disaster preparedness policies and enhances Taiwan’s disaster management ability.

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