The post-disaster emergency medical rescue (EMR) is critical for people’s lives. This paper presents a stochastic Petri net (SPN) model based on the process of the rescue structure and a Markov chain model (MC), which is applied to the optimization of the EMR process, with the aim of identifying the key activities of EMR. An isomorphic MC model is developed for measuring and evaluating the time performance of the EMR process during earthquakes with the data of the 2008 Wenchuan earthquake. This paper provides a mathematical approach to simulate the process and to evaluate the efficiency of EMR. Simultaneously, the expressions of the steady state probabilities of this system under various states are obtained based on the MC, and the variations of the probabilities are analyzed by changing the firing rates for every transition. Based on the concrete data of the event, the authors find the most time consuming and critical activities for EMR decisions. The model results show that the key activities can improve the efficiency of medical rescue, providing decision-makers with rescue strategies during the large scale earthquake.

灾后紧急医疗救援（EMR）对人们的生命至关重要。本文提出了一种基于救援结构过程的随机Petri网（SPN）模型和马尔可夫链模型（MC），将其应用于EMR过程的优化，旨在识别EMR的关键活动。利用 2008 年汶川地震数据，建立了同构 MC 模型，用于测量和评估地震期间 EMR 过程的时间性能。本文提供了一种数学方法来模拟该过程并评估 EMR 的效率。同时，基于MC得到了该系统在各种状态下的稳态概率表达式，并通过改变每个跃迁的激发率来分析概率的变化。根据事件的具体数据，作者发现 EMR 决策最耗时和最关键的活动。模型结果表明，重点活动可以提高医疗救援的效率，为决策者提供大地震期间的救援策略。