當大量傷患事件發生後，短時間內將會產生大量的受傷民眾，此時受限的醫療供給能量將無法滿足大量的醫療需求能量，因此為了有效的將醫療能量保留給真正需要醫療資源的傷患，將會在災區的附近設置臨時的檢傷站（Casualty Collection Point, CCP），當傷患從災區救出時將先送至檢傷站，藉由專業的檢傷人員將傷患分為輕度、中度、重度以及立即死亡的四種檢傷等級，並且優先將醫療資源保留給中度和重度的傷患，為了盡快將傷患送往醫院，因此在哪裡開設檢傷站以及稀缺資源的分配問題是在災後應變首須面對的一大課題。本研究參考臺灣消防隊救災流程，並以地震產生的多個災害點為例，在考量災後道路的失效可能性下，決定檢傷站的開設位置以及救護車/檢傷人員的資源分配，因為在災後影響傷患送到醫院的隨機因子相當多，例如傷患救出的順序、救護車的旅行時間等，因此本研究使用模擬最佳化的方法來解決研究的問題，利用離散事件模擬來建置模擬模型，透過模擬模型模擬災害發生後的關鍵救援行為，並提出了一種兩階段連續式的演算法來處理此問題，期望本研究能提供災害應變人員最佳的決策建議。

After a severe disaster strikes, a large number of casualties in need of urgent treatment, known as a mass casualty incident (MCI) event, gush out from multiple disaster areas in a very short period of time and overwhelm available resources of the local healthcare system. Therefore, this paper focuses on the effective design of casualty collection point (CCP) locations and the efficient allocation of limited emergency medical service (EMS) resources to transport the casualties quickly to appropriate hospitals and increase the survival rate of casualties for a rapid response. A hybrid simulation–optimization approach to optimize the CCP location and EMS resource allocation problem over mixed binary and integer feasible domains for the minimization of expected complete delivery time of all casualties from disaster region to hospital is presented in this work due to the stochastic and dynamic nature of the MCI system. A high-resolution stochastic discrete event simulation model considering time-varying stochastic casualty arrivals, random triage service time, and stochastic travel time caused by road network vulnerability is first constructed to describe a more detailed modeling of comprehensive MCI humanitarian logistics from the disaster regions to the hospitals. Then, a novel two-stage sequential algorithm, namely a combination of optimal computing budget allocation-based rapid-screening algorithm and adaptive particle global and hyperbox local search (ORSA-APGHLS), is developed to speed up convergence to the globally optimal solution under a limited simulation budget. We collaborate with the National Science and Technology Center for Disaster Reduction (NCDR) in Taiwan to conduct computational experiments to demonstrate the efficiency and efficacy of the proposed two-stage ORSA-APGHLS algorithm according to a potential earthquake scenario occurred in Tainan County in Taiwan. Through sensitivity analysis, the influence of different levels of scarce emergency medical resources and degrees of road damage on the expected complete delivery time of all casualties and the location-allocation decisions are investigated.

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