A robust optimization model for casualty distribution in a mass casualty incident

Document Type : Research Paper


1 Esfarayen University of Technology, Esfarayen, North Khorasan, Iran

2 Kermanshah University of Technology, Department of Industrial Engineering, Kermanshah, Iran



Due to increase in number and severity of disasters, managing the injured people immediately after a sudden-onset disaster is essential while there are few resources such as search and rescue and medical teams. These people are classified in the four triage groups. Uncertainty is an inevitable element in the chaotic environment after the disaster. This paper develops a robust stochastic optimization model to allocate the limited resources to the effected sites and casualty groups in the early aftermath of sudden-onset mass casualty incidents. Search and rescue operation and temporary treatment is considered in the model. Link disruption and facility unavailability in a dynamic environment are considered to make a model realistic. The robust model that tries to maintain the optimal solution under given scenarios close to its expected value. We incorporate the model and solution robustness in the model simultaneously. Numerical analysis experiments the model performance and the results are presented.


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