A metaheuristic-based approach for optimizing the allocation of emergency water reservoirs for fire following earthquake suppression - Ali Tanoumand; Mohammadreza Mashayekhi; Ali Majdi; Ehsan Noroozinejad Farsangi (Results in Engineering)
Given resource constraints, the need to minimize water access time, and the prevention of shortages, optimizing the distribution and density of water resources is considered a fundamental requirement for effective crisis management of fire following earthquakes (FFE). While no comprehensive and optimized model has been proposed in this area so far, this article presents a framework for optimizing the allocation of emergency water reservoirs for the suppression of FFE by integrating risk assessment and urban dynamics. The proposed framework identifies initial locations for the placement of emergency reservoirs, considering post-earthquake conditions. The optimal number and capacity of the reservoirs are determined through a robust FFE model calibrated with historical incident data and environmental characteristics. Within each urban area, a specific number of candidate locations are selected from the initial locations. Using a metaheuristic algorithm, the optimal allocation zones are identified based on the total distance from urban areas and the FFE risk factor. This approach resulted in improved overall system performance by reducing the time required to access water resources across the city and by ensuring that the maximum distances fall within the desired range (<4 km) as defined by the distance classification framework. By applying influential criteria and conducting location analysis within the allocated zones, the final points are identified as the designated locations for reservoir placement. The implementation of the proposed framework within the Tehran urban area resulted in the allocation of 90 emergency water reservoirs, each with a capacity of 100 cubic meters. This approach effectively and efficiently addresses water requirements for the suppression of FFEs, with a total storage volume of just 9000 cubic meters.