论文标题
OpenEms：用于救护车地点的两阶段随机且可靠的优化的开源软件包，并与Austin-Travis County EMS数据相关
OpenEMS: an open-source Package for Two-Stage Stochastic and Robust Optimization for Ambulance Location and Routing with Applications to Austin-Travis County EMS Data
论文作者
论文摘要
紧急医疗系统（EMS）提供至关重要的院前保健和运输。更快的EMS响应时间提供了更快的院前护理，从而提高了存活率。我们通过解决两个阶段随机和健壮的线性程序来提供最佳的救护车站和路由决策来减少响应时间。尽管关于救护车系统的运营研究已有数十年历史了，但开源代码几乎没有模拟。我们通过与德克萨斯州的奥斯汀 - 特拉维斯县EMS（ATCEMS）合作发布Openems开始弥合这一差距，这是一条端到端的管道，以优化救护车战略决策。它包括数据处理，优化和校准模拟。我们希望这个开源框架能够促进与EMS的未来研究。最后，我们在德克萨斯州奥斯汀市提供了详细的案例研究。我们发现，最佳驻扎将增加响应时间为88.02秒。此外，我们设计了奥斯汀EMS必须永久添加或从其车队中删除一辆救护车的情况下的最佳策略。
Emergency Medical Systems (EMS) provide crucial pre-hospital care and transportation. Faster EMS response time provides quicker pre-hospital care and thus increases survival rate. We reduce response time by providing optimal ambulance stationing and routing decisions by solving two stage stochastic and robust linear programs. Although operational research on ambulance systems is decades old, there is little open-source code and consistency in simulations. We begin to bridge this gap by publishing OpenEMS, in collaboration with the Austin-Travis County EMS (ATCEMS) in Texas, an end-to-end pipeline to optimize ambulance strategic decisions. It includes data handling, optimization, and a calibrated simulation. We hope this open source framework will foster future research with and for EMS. Finally, we provide a detailed case study on the city of Austin, Texas. We find that optimal stationing would increase response time by 88.02 seconds. Further, we design optimal strategies in the case where Austin EMS must permanently add or remove one ambulance from their fleet.
