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Stochastic ambulance dispatching and routing in mass casualty incident under road vulnerability
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Stochastic ambulance dispatching and routing in mass casualty incident under road vulnerability

Kuo-Hao Chang, Tzu-Li Chen, Yi-Ting LeeTzu-Yin Chang
Journal of the Operational Research Society
2024

摘要

ambulance dispatching and routing column generation mass casualty incident Practice of operational research road vulnerability sample average approximation simulation stochastic programming Modeling and Simulation Strategy and Management Statistics Probability and Uncertainty Management Science and Operations Research
This paper investigates the stochastic ambulance dispatching and routing (SADR) problem with multiple casualty collection points in the mass casualty incidents (MCI) under uncertainty of road vulnerability and traffic congestion caused by an earthquake. A two-stage stochastic mixed-integer nonlinear programming model is formulated to derive a reliable and high-quality ambulance scheduling, dispatching and routing solution for maximizing expected number of survivors of all casualties. An integrated simulation optimization approach combining a data-driven travel time scenario generation algorithm, sample average approximation, and a column-generation-based heuristic method is developed to efficiently solve this complicated two-stage SADR model with a nonlinear objective function and continuous travel time distributions. Collaborating with the National Science and Technology Center for Disaster Reduction (NCDR), an empirical study using a potential real-world earthquake scenario occurring in Taiwan is conducted to demonstrate the usefulness and effectiveness of our proposed model and solution approach compared to the deterministic model and two current-practice heuristics.

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