Minimizing response time to accidents in big cities: a two ranked level model for allocating fire stations
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ORIGINAL PAPER
Minimizing response time to accidents in big cities: a two ranked level model for allocating fire stations Samira Bolouri 1
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Alireza Vafaeinejad 2
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Aliasghar Alesheikh 3
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Hossein Aghamohammadi 4
Received: 22 March 2019 / Accepted: 15 July 2020 # Saudi Society for Geosciences 2020
Abstract In crowded cities, like Tehran, when a major accident occurs, such as a fire, the response from more than one fire station is usually needed at the scene. The present study focuses on demand allocation to fire stations at two ranked levels to determine the priorities of fire stations to service relevant demands. To solve this problem, this paper uses the Vector Assignment Ordered Median Problem (VAOMP), a new location–allocation model that can allocate demands to facilities at several ranked levels, based on the particular objective function. Thus, this paper uses the meta-heuristic methods of Tabu and genetic algorithms to minimize the arrival time from fire stations to demands, at two levels, at up to 5 min in the GIS environment of the 21st and 22nd districts of Tehran. The optimum parameters for each algorithm were obtained through sensitivity analysis. The results of applying the model with two algorithms in these districts with 10 existing fire stations and 336,600 inhabitants showed that the current stations are insufficient for two levels of service and that 52,840 people at level 1 and 81,320 people at level 2 have no access to services. As such, the results of two algorithms for relocation–reallocation analysis at two levels with different weightings for 13 potential and existing fire stations showed that at least 3 new stations need to be created. Furthermore, the genetic algorithm produced qualitatively superior results, in optimal values, the accuracy of allocation and timeframe, compared with the Tabu algorithm. Keywords Two ranked level allocation . Vector Assignment Ordered Median Problem . Tabu search and genetic algorithm . GIS
Introduction Responsible Editor: Biswajeet Pradhan * Samira Bolouri [email protected] * Alireza Vafaeinejad [email protected] Aliasghar Alesheikh [email protected] Hossein Aghamohammadi [email protected] 1
Civil Engineering Department, Tehran North Branch, Islamic Azad University, Tehran, Iran
2
Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
3
Department of Geospatial Information Systems, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
4
Science and Research Branch, Islamic Azad University, Tehran, Iran
Planning theory and practice focus mainly on urban areas (Beyazli et al. 2017). Human activities have caused great changes on the environment, and the excellent location of service providers can avoid further environmental damages (Akbary et al. 2018). At the same time, the probability of accidents occurring is higher in large cities with large populations. If the relief forces and service providers are not located in the right place or if t
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