Abstract
Introduction. Resource allocation is a challenging topic in the search and rescue (SAR) in post-disaster process, especially in situations with sparse infrastructure and dynamic demanding requirement. Previous studies have well demonstrated the need to improve the SAR decision-making process in these situations. However, a challenge that current models are facing is how to select target areas considering the random distribution of survivors with little information or coordination.
Method. This paper makes a first attempt to compare the different models in SAR process, where SAR teams are supposed to operate independently or are dispatched by a central system. The paper uses the dynamic network models, which can avoid the shortcoming of normal random search, for SAR strategy analyses.
Results. The numerical example shows that when information is uncertain, central dispatch easily leads to low efficiency in SAR management. Besides, quantity priority is proved to be more efficient than normal random search, especially when the distribution of survivors is not even.
Conclusion. The findings of this paper provide important information for selecting effective analytical models in SAR management to save survivors.
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Acknowledgements
The authors appreciate the funding support from the National Natural Science Foundation of China (51508122), Guangxi science and technology projects (1524800210, AB16380280), Guangxi Natural Science Foundation (Grant No. 2015GXNSFBA139216), as well as The Scientific research project of National Ministry of Housing and Urban-Rural Construction (2017-K2-009). Scientific Research Project of Nanning University (2018XJ39).
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Liu, Q., Chen, J., Peng, G., Wan, Q., Liang, Q. (2018). Evaluating the Search and Rescue Strategies of Post Disaster. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_18
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