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ISPRS Int. J. Geo-Inf. 2018, 7(2), 44; https://doi.org/10.3390/ijgi7020044

The Ordered Capacitated Multi-Objective Location-Allocation Problem for Fire Stations Using Spatial Optimization

1
Department of GIS & RS, Science & Research Branch, Islamic Azad University, Tehran, Iran
2
Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
3
Department of GIS Engineering, K. N. Toosi University of Technology, Tehran, Iran
*
Author to whom correspondence should be addressed.
Received: 16 December 2017 / Revised: 26 January 2018 / Accepted: 28 January 2018 / Published: 31 January 2018
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Abstract

Determining the positions of facilities, and allocating demands to them, is a vitally important problem. Location-allocation problems are optimization NP-hard procedures. This article evaluates the ordered capacitated multi-objective location-allocation problem for fire stations, using simulated annealing and a genetic algorithm, with goals such as minimizing the distance and time as well as maximizing the coverage. After tuning the parameters of the algorithms using sensitivity analysis, they were used separately to process data for Region 11, Tehran. The results showed that the genetic algorithm was more efficient than simulated annealing, and therefore, the genetic algorithm was used in later steps. Next, we increased the number of stations. Results showed that the model can successfully provide seven optimal locations and allocate high demands (280,000) to stations in a discrete space in a GIS, assuming that the stations’ capacities are known. Following this, we used a weighting program so that in each repetition, we could allot weights to each target randomly. Finally, by repeating the model over 10 independent executions, a set of solutions with the least sum and the highest number of non-dominated solutions was selected from among many non-dominated solutions as the best set of optimal solutions. View Full-Text
Keywords: ordered capacitated multi-objective location-allocation; sensitivity analysis; genetic algorithm; simulated annealing; GIS; non-dominated ordered capacitated multi-objective location-allocation; sensitivity analysis; genetic algorithm; simulated annealing; GIS; non-dominated
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Bolouri, S.; Vafaeinejad, A.; Alesheikh, A.A.; Aghamohammadi, H. The Ordered Capacitated Multi-Objective Location-Allocation Problem for Fire Stations Using Spatial Optimization. ISPRS Int. J. Geo-Inf. 2018, 7, 44.

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