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Algorithms 2017, 10(4), 125; https://doi.org/10.3390/a10040125

Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

School of Economics and Management, China University of Geosciences, Wuhan 430074, China
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Received: 1 September 2017 / Revised: 10 November 2017 / Accepted: 12 November 2017 / Published: 15 November 2017
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Abstract

In this paper, we optimize the search and rescue (SAR) in disaster relief through agent-based simulation. We simulate rescue teams’ search behaviors with the improved Truncated Lévy walks. Then we propose a cooperative rescue plan based on a distributed auction mechanism, and illustrate it with the case of landslide disaster relief. The simulation is conducted in three scenarios, including “fatal”, “serious” and “normal”. Compared with the non-cooperative rescue plan, the proposed rescue plan in this paper would increase victims’ relative survival probability by 7–15%, increase the ratio of survivors getting rescued by 5.3–12.9%, and decrease the average elapsed time for one site getting rescued by 16.6–21.6%. The robustness analysis shows that search radius can affect the rescue efficiency significantly, while the scope of cooperation cannot. The sensitivity analysis shows that the two parameters, the time limit for completing rescue operations in one buried site and the maximum turning angle for next step, both have a great influence on rescue efficiency, and there exists optimal value for both of them in view of rescue efficiency. View Full-Text
Keywords: disaster relief; simulation optimization; Truncated Lévy walks; distributed auction mechanism; cooperative rescue disaster relief; simulation optimization; Truncated Lévy walks; distributed auction mechanism; cooperative rescue
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Tang, J.; Zhu, K.; Guo, H.; Liao, C.; Zhang, S. Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism. Algorithms 2017, 10, 125.

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