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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Autores principales: CelsoSatoshi Sakuraba, AndréaCynthia Santos, Christian Prins, Lucie Bouillot, Arnaud Durand, Bernard Allenbach
Formato: article
Lenguaje:EN
Publicado: Elsevier 2016
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Acceso en línea:https://doaj.org/article/260849c6292b4cfeb8eabae26102135e
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spelling 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)
institution DOAJ
collection DOAJ
language EN
topic 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
spellingShingle 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
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AT luciebouillot roadnetworkemergencyaccessibilityplanningafteramajorearthquake
AT arnauddurand roadnetworkemergencyaccessibilityplanningafteramajorearthquake
AT bernardallenbach roadnetworkemergencyaccessibilityplanningafteramajorearthquake
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