Road network emergency accessibility planning after a major earthquake
In the aftermath of disasters such as major earthquakes, several roads may be blocked by rubble and the population tends to search refugee in certain gathering points of the city. Road network accessibility becomes an important issue for logistic operations, specially on the first days after the qua...
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2016
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oai:doaj.org-article:260849c6292b4cfeb8eabae26102135e2021-12-02T05:00:57ZRoad network emergency accessibility planning after a major earthquake2192-440610.1007/s13675-016-0070-2https://doaj.org/article/260849c6292b4cfeb8eabae26102135e2016-09-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2192440621000691https://doaj.org/toc/2192-4406In the aftermath of disasters such as major earthquakes, several roads may be blocked by rubble and the population tends to search refugee in certain gathering points of the city. Road network accessibility becomes an important issue for logistic operations, specially on the first days after the quake, when the relief distribution is crucial for survival. This study focused on the Road Emergency Rehabilitation Problem, divided into the Road Network Accessibility Problem (RNAP) and the Work-troops Scheduling Problem (WSP). The first one consists in finding traversable paths for relief teams to reach the population, and the later generates a repairing schedule to improve access to refugee areas. The contributions of this study are two-fold: we present the process of transcribing satellite imagery data into graphs, and mathematical formulations for the RNAP and WSP, along with heuristics to solve the WSP. The proposed methods are able to handle large-scale graphs in an acceptable running time for real scenarios. They are tested on simulated instances and on the graph of Port-au-Prince, with more than 10,000 vertices and edges. The Port-au-Prince graph was generated from satellite images obtained by the International Charter “Space and Major Disasters” a few hours after the 2010 earthquake.CelsoSatoshi SakurabaAndréaCynthia SantosChristian PrinsLucie BouillotArnaud DurandBernard AllenbachElsevierarticle90B06 Transportation, logistics90B10 Network models, deterministic90B90 Case-oriented studies90C11 Mixed integer programming90C90 Applications of mathematical programmingApplied mathematics. Quantitative methodsT57-57.97Electronic computers. Computer scienceQA75.5-76.95ENEURO Journal on Computational Optimization, Vol 4, Iss 3, Pp 381-402 (2016) |
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DOAJ |
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90B06 Transportation, logistics 90B10 Network models, deterministic 90B90 Case-oriented studies 90C11 Mixed integer programming 90C90 Applications of mathematical programming Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95 |
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90B06 Transportation, logistics 90B10 Network models, deterministic 90B90 Case-oriented studies 90C11 Mixed integer programming 90C90 Applications of mathematical programming Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95 CelsoSatoshi Sakuraba AndréaCynthia Santos Christian Prins Lucie Bouillot Arnaud Durand Bernard Allenbach Road network emergency accessibility planning after a major earthquake |
description |
In the aftermath of disasters such as major earthquakes, several roads may be blocked by rubble and the population tends to search refugee in certain gathering points of the city. Road network accessibility becomes an important issue for logistic operations, specially on the first days after the quake, when the relief distribution is crucial for survival. This study focused on the Road Emergency Rehabilitation Problem, divided into the Road Network Accessibility Problem (RNAP) and the Work-troops Scheduling Problem (WSP). The first one consists in finding traversable paths for relief teams to reach the population, and the later generates a repairing schedule to improve access to refugee areas. The contributions of this study are two-fold: we present the process of transcribing satellite imagery data into graphs, and mathematical formulations for the RNAP and WSP, along with heuristics to solve the WSP. The proposed methods are able to handle large-scale graphs in an acceptable running time for real scenarios. They are tested on simulated instances and on the graph of Port-au-Prince, with more than 10,000 vertices and edges. The Port-au-Prince graph was generated from satellite images obtained by the International Charter “Space and Major Disasters” a few hours after the 2010 earthquake. |
format |
article |
author |
CelsoSatoshi Sakuraba AndréaCynthia Santos Christian Prins Lucie Bouillot Arnaud Durand Bernard Allenbach |
author_facet |
CelsoSatoshi Sakuraba AndréaCynthia Santos Christian Prins Lucie Bouillot Arnaud Durand Bernard Allenbach |
author_sort |
CelsoSatoshi Sakuraba |
title |
Road network emergency accessibility planning after a major earthquake |
title_short |
Road network emergency accessibility planning after a major earthquake |
title_full |
Road network emergency accessibility planning after a major earthquake |
title_fullStr |
Road network emergency accessibility planning after a major earthquake |
title_full_unstemmed |
Road network emergency accessibility planning after a major earthquake |
title_sort |
road network emergency accessibility planning after a major earthquake |
publisher |
Elsevier |
publishDate |
2016 |
url |
https://doaj.org/article/260849c6292b4cfeb8eabae26102135e |
work_keys_str_mv |
AT celsosatoshisakuraba roadnetworkemergencyaccessibilityplanningafteramajorearthquake AT andreacynthiasantos roadnetworkemergencyaccessibilityplanningafteramajorearthquake AT christianprins roadnetworkemergencyaccessibilityplanningafteramajorearthquake AT luciebouillot roadnetworkemergencyaccessibilityplanningafteramajorearthquake AT arnauddurand roadnetworkemergencyaccessibilityplanningafteramajorearthquake AT bernardallenbach roadnetworkemergencyaccessibilityplanningafteramajorearthquake |
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