Scheduling optimization for joint transport of heterogeneous injured patients by ambulances and rescue aircrafts

Abstract

This paper studies the scheduling optimization in casualty transportation after large-scale natural disasters, with a particular focus on the impact of injury heterogeneity on dispatch decisions. By considering different deprivation cost functions, we quantify the economic value of the pain endured by casualties before receiving medical treatment. An exact mathematical programming model is developed to minimize total economic and deprivation costs and optimize transportation strategies for critically and mildly injured patients. This model incorporates a collaborative ambulance-air rescue transportation mode that prioritizes air rescue for critically injured patients under emergency medical requirements. By using the historical medical rescue data from Jianyang City in Sichuan Province of China, we verify the effectiveness of the model through a case study by CPLEX 12.8.0 solver. Sensitivity analysis further provides some theoretical foundations and practical guidance for post-disaster casualty transportation planning.