Faris Aljehani, Akshay Krishnakumar
Abstract: Epidemic outbreaks in a region tend to overwhelm existing medical services due to the sudden surge of patients suffering from a particular disease. Providing necessary care for these patients while handling the usual patient flow can cause depletion of certain types of medical resources and ultimately loss of life. In this project, we develop a linear programming model that seeks to maximize access to treatment between regions in Michigan, across multiple diseases and resource constraints.
Isaac Smith, Ziang Xu, Lanxuan Zhao
Abstract: The team was given three options for linear programs: optimal screening in a pandemic, medical resource re-allocation, and lunch delivery during school lockdown. Medical resource re-allocation was chosen due to recent events surrounding ventilators and personal protective equipment (PPE). This problem entails a new virus infecting citizens and hospitals needing to make the decision of whether to treat new patients or existing patients. Within that decision, multiple cities can send resources to each other. This mixed- integer problem will show the optimal amount of resources to send in each period and which patients should be treated to minimize the total number of deaths. In the model created, there are six two-week periods, eight cities, three medical resources, and two patient types to consider.