Improving Healthcare Systems' Performance during Mass Casualty Incidents using a Simulation, Optimization, and Machine Learning approach

洪水、地震、化学品泄漏或流行病等灾害事件通常发生在世界各地。这些事件导致大量的人在短时间内受伤。因此，对保健服务的需求将很高。在这些事件期间，医疗系统中产生的繁重工作量扰乱了医疗系统的功能，使得医院等医疗中心无法为患者/受伤人员提供适当的医疗和护理服务。这危害人类健康，甚至可能导致生命损失。本研究旨在以科学的认识方法来解决这一问题，运用定量的方法来提高卫生院的绩效。我们期望研究结果能够改善卫生服务的提供，防止灾害事件中的生命损失。

Disaster events such as floods, earthquakes, chemical spills, or epidemics usually take place all aroundthe world. Such events lead to the injury of a large number of people in a short amount of time. As aresult, there will be a high level of demand for health services. The heavy workload created in thehealthcare system during these incidents disrupts the function of the healthcare systems so that thehealth centers such as hospitals cannot provide medical treatment and care services to thepatients/injured people properly. This endangers human health and may even lead to the loss of humanlives. In this research project, we address this problem in a scientific way of knowing, using quantitativemethods to improve the performance of health centers. We expect the results of the study to improvethe delivery of health services and prevent loss of life during disaster incidents.