Ambulances Deployment Problems: Categorization, Evolution and Dynamic Problems Review

In this paper, an analytic review of the recent methodologies tackling problem dynamic allocation ambulances was carried out. Considering that state-of-the-art is moving to deal with more extensive and problems address in a better way real-life instances, research looks identify evolution applications kind once basic models are explored. This allowed us most developments critical gaps be addressed. sense, it essential point out location emergency medical services (EMS) nowadays relevant topic considering its impact on healthcare system outcomes. Issues related forecasting, simulation, heterogeneous fleets, robustness, solution speed for problems, stand identified gaps. Applications machine learning deployment challenges during epidemic outbreaks such as SARS COVID-19 were also At same time, proposed notation tries tackle fact word work refers model many occasions. The eases comparison between different proposals found literature.