Abstract
The staging (or locating) of air ambulances throughout a jurisdiction of responsibility is widely accepted to be influential in achieving positive patient outcomes. Traditionally, the assignment of bases is made as a function of either population density or by maximizing coverage. This work leverages historical data detailing missions executed by an air ambulance service to identify locations for bases that minimize the total distances flown by the fleet throughout the study period. Given the known computational complexity of the problem (NP-hard), and volume of data being examined, a genetic algorithm was chosen due to its demonstrated effectiveness at solving combinatorial problems. Over the course of the evolutionary process, the objection function value of the population’s best-performing chromosome decreased by 24%.
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Pond, G.T., McQuat, G. (2018). Optimizing Fleet Staging of Air Ambulances in the Province of Ontario. In: Fagan, D., MartĂn-Vide, C., O'Neill, M., Vega-RodrĂguez, M.A. (eds) Theory and Practice of Natural Computing. TPNC 2018. Lecture Notes in Computer Science(), vol 11324. Springer, Cham. https://doi.org/10.1007/978-3-030-04070-3_17
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