Robust Design of Adaptive Risk-averse Pre-hospital Care Network
In order to improve the emergency response capabilities of the medical emergency system under sudden large-scale demand scenarios,a pre-hospital care network design method based on a two-stage adaptive risk-averse robust optimization model was proposed.For uncertain random emergency demands,a worst-case robust conditional value-at-risk model was constructed through a scenario-based method to avoid extreme risks of unmet demands and ensure the service capabilities of the system.An equivalent robust counterpart was proposed according to the linear duality theory to simplify the solution process.Finally,the validity and reliability of the model were verified based on a specific numerical case in a city.Through comparative analysis and sensitivity analysis,it is found that the adaptive model has a higher demand satisfaction rate and a lower loss risk costs than the risk-neutral model and the general stochastic risk aversion model.The optimization planning significantly improves emergency response efficiency and demand coverage under uncertain environments.
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