Two-stage Stochastic Optimization for the Allocation of Medical Assets in Steady-state Combat Operations
Autor: | M. Nicholas Coppola, Lawrence V. Fulton, Leon S. Lasdon, Reuben R. McDaniel |
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Rok vydání: | 2010 |
Předmět: | |
Zdroj: | The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology. 7:89-102 |
ISSN: | 1557-380X 1548-5129 |
DOI: | 10.1177/1548512910364390 |
Popis: | In this study we describe a stochastic optimization model for the relocation of deployable military hospitals, the reallocation of hospital beds, and the emplacement of tactical medical evacuation assets (medical evacuation helicopters and ground ambulances) during steady-state military combat operations (stability operations). The network model is built around an intuitive objective function, one that is derived from military doctrine. The objective to be minimized is the time traveled, weighted by patient severity, from the evacuation site to the point of injury and onward to the hospital location. The optimal solution also determines the number of air and ground ambulances and the hospital beds of each type required at each selected site. Since future casualty locations, numbers, and severities are uncertain, this information is treated as a number of casualty scenarios with assigned scenario probabilities. The number, location, and severities of casualties can be randomly generated, or provided as part of a planning process. The model then seeks a single set of hospital and vehicle locations, plus the paths the evacuation assets should take in each scenario, which minimize expected travel time over all scenarios. The scenario generator is based on realistic historical data from Operation Iraqi Freedom. Since mobile hospitals provide the primary surgical treatment intervention while dedicated ground and air evacuation assets provide the transportation along evacuation paths, the study objective is important for military medical planners, especially those involved in tactical medical evacuation and treatment planning. |
Databáze: | OpenAIRE |
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