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.
Highlights
Search and rescue of victims in large-scale disasters is of great importance in disaster relief.The research of disaster relief has focused mostly on emergency supplies reserves, location problems, emergency transportation, resource allocation and evacuation [1,2,3,4,5,6,7], which has provided an important theoretical foundation for disaster relief and improved rescue efficiency for sure
Before we built the conceptual model, we had gathered a lot of detailed information about SAR through the interviews carried out with first responders and experts who specialize in on-site search and rescue in disaster
The health condition of a victim could deteriorate continuously, the survival probability will decrease with time, and they may be dead as time passes
Summary
The research of disaster relief has focused mostly on emergency supplies reserves, location problems, emergency transportation, resource allocation and evacuation [1,2,3,4,5,6,7], which has provided an important theoretical foundation for disaster relief and improved rescue efficiency for sure. Many approaches for the task allocation problem have been proposed, such as contract net protocol [8,9], intelligent algorithm-based approaches [10,11,12,13] and auction-based approaches [14,15,16], etc. Liang and Kang [8] have proposed an improved contract net protocol for task allocation in agent-oriented unmanned underwater vehicle (UUV) swarm system. Su et al [9] employed contract net protocol for task allocation at an assembly point when adjusting group members periodically
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