This work aims to tackle the following two research questions regarding post-disaster rescues: how to optimize the rescue team dispatch based on the specialties of the team and the type of damage incurred, and how to optimize the allocation of injured patients to hospitals based on their symptoms, the rescue teams allocated, and the abilities of the hospitals to minimize fatalities. Rather than handling these two problems separately, we formulate them into an integrated system. A real-coded genetic algorithm is applied to minimize the estimated transport time in terms of distance, and the disparity between resource supply and demand. A set of scenarios is simulated and analyzed to provide insight for policy makers. Further, the simulated results can be used for future post-disaster medical assistance training.
|ジャーナル||Journal of Advanced Computational Intelligence and Intelligent Informatics|
|出版ステータス||Published - 2017 11|
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Artificial Intelligence