A maximum expected covering problem for locating and dispatching two classes of military medical evacuation air assets

A Maximum Expected Covering Problem for Locating and Dispatching Two Classes of Military Medical Evacuation Air Assets Report Title Military medical evacuation (MEDEVAC) systems respond to casualty incidents and transport the most urgent casualties to a medical treatment facility via multiple types of air ambulance assets. Military MEDEVAC systems are subject to an uncertain number of service calls and each service call demands different system operations depending on type and the priority level. Therefore, military medical planners need an air MEDEVAC asset management system that determines how to dispatch multiple types of air assets to prioritized service calls to maintain a high likelihood of survival of the most urgent casualties. To reach this goal, we propose a novel binary linear programming (BLP) model to optimally locate two types of air assets and construct response districts using a dispatch preference list. Additionally, the BLP model balances the workload among assets and enforces contiguity in the first assigned locations for each air asset. The objective of the BLP model is to maximize the proportion of high-priority casualties responded to within a pre-specified time threshold while meeting performance benchmarks to other types of casualties. A spatial queuing approximation model is derived to provide inputs to the BLP model, which thus reflects the underlying queuing dynamics of the system. We illustrate the model and algorithms with a computational example that reflects realistic military data. Optimization Letters manuscript No. (will be inserted by the editor) A Maximum Expected Covering Problem for Locating and Dispatching Two Classes of Military Medical Evacuation Air Assets Benjamin C. Grannan · Nathaniel D. Bastian · Laura A. McLay Received: date / Accepted: date Abstract Military medical evacuation (MEDEVAC) systems respond to casualty incidents and transport the most urgent casualties to a medical treatment facility via multiple types of air ambulance assets. Military MEDEVAC systems are subject to an uncertain number of service calls and each service call demands different system operations depending on type and the priority level. Therefore, military medical planners need an air MEDEVAC asset management system that determines how to dispatch multiple types of air assets to prioritized service calls to maintain a high likelihood of survival of the most urgent casualties. To reach this goal, we propose a novel binary linear programming (BLP) model to optimally locate two types of air assets and construct response districts using a dispatch preference list. Additionally, the BLP model balances the workload among assets and enforces contiguity in the first assigned locations for each air asset. The objective of the BLP model is to maximize the proportion of high-priority casualties responded to within a pre-specified time threshold while meeting performance benchmarks to other types of casualties. A spatial queuing approximation model is derived to provide inputs to the BLP model, which thus reflects the underlying queuing dynamics of the system. We illustrate the model and algorithms with a computational example that reflects realistic military data.