OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)

The successful conduct of a rescue mission in urban areas is directly related to the timely deployment of equipment and personnel to the incident location which justifies the quest for optimum path selection for emergency purposes. In this study, it is attempted to use Ant Colony Optimization (ACO)...

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Main Authors: N. Zarrinpanjeh, F. Dadrass Javan, A. Naji, H. Azadi, P. De Maeyer, F. Witlox
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1285/2020/isprs-archives-XLIII-B3-2020-1285-2020.pdf
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author N. Zarrinpanjeh
F. Dadrass Javan
F. Dadrass Javan
A. Naji
H. Azadi
P. De Maeyer
F. Witlox
author_facet N. Zarrinpanjeh
F. Dadrass Javan
F. Dadrass Javan
A. Naji
H. Azadi
P. De Maeyer
F. Witlox
author_sort N. Zarrinpanjeh
collection DOAJ
description The successful conduct of a rescue mission in urban areas is directly related to the timely deployment of equipment and personnel to the incident location which justifies the quest for optimum path selection for emergency purposes. In this study, it is attempted to use Ant Colony Optimization (ACO) to find the optimum paths between fire stations and incident locations. It is also attempted to build up an evaluation tool using ACO to detect critical road segments that the overall accessibility to fire station services throughout the urban area is constituted upon their excellent functionality. Therefore, an ACO solution is designed to find optimum paths between the fire station and some randomly distributed incident locations. Regarding different variants of ACO, the algorithm enjoys the Simple Ant Colony Optimization deployment strategy combined with Ant Algorithm Transition rules. Iteration best pheromone updating is also used as the pheromone reinforcement strategy. The cost function used to optimize the path considers the shortest Euclidean distance on the network. The results explicitly state that the proposed method is successful to create the optimum path in 95.45 percent of all times, compared to Dijkstra deterministic approaches. Moreover, the pheromone map as an indicator of the criticality of road elements is generated and discussed. Visual inspection shows that the pheromone map is verified as the road criticality map concerning fire station access to the region and therefore pre-emptive measures can be defined by analyzing the generated pheromone map.
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spelling doaj.art-64eb3358f4a04c5ba820eaf8cba913962022-12-21T18:40:06ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B3-20201285129110.5194/isprs-archives-XLIII-B3-2020-1285-2020OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)N. Zarrinpanjeh0F. Dadrass Javan1F. Dadrass Javan2A. Naji3H. Azadi4P. De Maeyer5F. Witlox6Department of Geomatics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranDepartment of Surveying and Geomatics Engineering, University College of Engineering, University of Tehran, Tehran, IranDepartment of Geography, Ghent University, Ghent, BelgiumDepartment of Geomatics Engineering, Ramsar Branch, Islamic Azad University, Ramsar, IranDepartment of Geography, Ghent University, Ghent, BelgiumDepartment of Geography, Ghent University, Ghent, BelgiumDepartment of Geography, Ghent University, Ghent, BelgiumThe successful conduct of a rescue mission in urban areas is directly related to the timely deployment of equipment and personnel to the incident location which justifies the quest for optimum path selection for emergency purposes. In this study, it is attempted to use Ant Colony Optimization (ACO) to find the optimum paths between fire stations and incident locations. It is also attempted to build up an evaluation tool using ACO to detect critical road segments that the overall accessibility to fire station services throughout the urban area is constituted upon their excellent functionality. Therefore, an ACO solution is designed to find optimum paths between the fire station and some randomly distributed incident locations. Regarding different variants of ACO, the algorithm enjoys the Simple Ant Colony Optimization deployment strategy combined with Ant Algorithm Transition rules. Iteration best pheromone updating is also used as the pheromone reinforcement strategy. The cost function used to optimize the path considers the shortest Euclidean distance on the network. The results explicitly state that the proposed method is successful to create the optimum path in 95.45 percent of all times, compared to Dijkstra deterministic approaches. Moreover, the pheromone map as an indicator of the criticality of road elements is generated and discussed. Visual inspection shows that the pheromone map is verified as the road criticality map concerning fire station access to the region and therefore pre-emptive measures can be defined by analyzing the generated pheromone map.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1285/2020/isprs-archives-XLIII-B3-2020-1285-2020.pdf
spellingShingle N. Zarrinpanjeh
F. Dadrass Javan
F. Dadrass Javan
A. Naji
H. Azadi
P. De Maeyer
F. Witlox
OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
title_full OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
title_fullStr OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
title_full_unstemmed OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
title_short OPTIMUM PATH DETERMINATION TO FACILITATE FIRE STATION RESCUE MISSIONS USING ANT COLONY OPTIMIZATION ALGORITHMS (CASE STUDY: CITY OF KARAJ)
title_sort optimum path determination to facilitate fire station rescue missions using ant colony optimization algorithms case study city of karaj
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1285/2020/isprs-archives-XLIII-B3-2020-1285-2020.pdf
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