Hooshangi, N; Mahdizadeh Gharakhanlou, N and Ghaffari-Razin, S R (2024) Urban search and rescue (USAR) simulation in earthquake environments using queuing theory: estimating the appropriate number of rescue teams. International Journal of Disaster Resilience in the Built Environment, 15(1), pp. 1-18. ISSN 1759-5916
Abstract
Purpose: The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation. Design/methodology/approach: In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations. Findings: The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate. Originality/value: The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.
Item Type: | Article |
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Uncontrolled Keywords: | disaster risk reduction; earthquake damage; number of rescuers; queuing theory; survival rate; urban search and rescue |
Date Deposited: | 11 Apr 2025 17:13 |
Last Modified: | 11 Apr 2025 17:13 |