Solution methodologies for debris removal in disaster response

During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deci...

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Autores principales:	Nihal Berktaş, BaharYetiş Kara, OyaEkin Karaşan
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2016
Materias:	90C11 90C90 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/c28129bf4c7345909ed0535fb97442ef
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spelling	oai:doaj.org-article:c28129bf4c7345909ed0535fb97442ef2021-12-02T05:00:57ZSolution methodologies for debris removal in disaster response2192-440610.1007/s13675-016-0063-1https://doaj.org/article/c28129bf4c7345909ed0535fb97442ef2016-09-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2192440621000708https://doaj.org/toc/2192-4406During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deciding which roads to clean to transport relief items is crucial to diminish the negative impact of a disaster on human health. Despite the significance of the problem during response phase, in the literature debris removal is mostly studied in the recovery or the reconstruction phases of a disaster. The aim of this study is providing solution methodologies for debris removal problem in the response phase in which effective and fast relief routing is of utmost importance. In particular, debris removal activities on certain blocked arcs have to be scheduled to reach a set of critical nodes such as schools and hospitals. To this end, two mathematical models are developed with different objectives. The first model aims to minimize the total time spent to reach all the critical nodes whereas the second minimizes the weighted sum of visiting times where weights indicate the priorities of critical nodes. Since obtaining solutions quickly is important in the early post-disaster, heuristic algorithms are also proposed. Two data sets belonging to Kartal and Bakırköy districts of İstanbul are used to test the mathematical models and heuristics.Nihal BerktaşBaharYetiş KaraOyaEkin KaraşanElsevierarticle90C1190C90Applied mathematics. Quantitative methodsT57-57.97Electronic computers. Computer scienceQA75.5-76.95ENEURO Journal on Computational Optimization, Vol 4, Iss 3, Pp 403-445 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	90C11 90C90 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
spellingShingle	90C11 90C90 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95 Nihal Berktaş BaharYetiş Kara OyaEkin Karaşan Solution methodologies for debris removal in disaster response
description	During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deciding which roads to clean to transport relief items is crucial to diminish the negative impact of a disaster on human health. Despite the significance of the problem during response phase, in the literature debris removal is mostly studied in the recovery or the reconstruction phases of a disaster. The aim of this study is providing solution methodologies for debris removal problem in the response phase in which effective and fast relief routing is of utmost importance. In particular, debris removal activities on certain blocked arcs have to be scheduled to reach a set of critical nodes such as schools and hospitals. To this end, two mathematical models are developed with different objectives. The first model aims to minimize the total time spent to reach all the critical nodes whereas the second minimizes the weighted sum of visiting times where weights indicate the priorities of critical nodes. Since obtaining solutions quickly is important in the early post-disaster, heuristic algorithms are also proposed. Two data sets belonging to Kartal and Bakırköy districts of İstanbul are used to test the mathematical models and heuristics.
format	article
author	Nihal Berktaş BaharYetiş Kara OyaEkin Karaşan
author_facet	Nihal Berktaş BaharYetiş Kara OyaEkin Karaşan
author_sort	Nihal Berktaş
title	Solution methodologies for debris removal in disaster response
title_short	Solution methodologies for debris removal in disaster response
title_full	Solution methodologies for debris removal in disaster response
title_fullStr	Solution methodologies for debris removal in disaster response
title_full_unstemmed	Solution methodologies for debris removal in disaster response
title_sort	solution methodologies for debris removal in disaster response
publisher	Elsevier
publishDate	2016
url	https://doaj.org/article/c28129bf4c7345909ed0535fb97442ef
work_keys_str_mv	AT nihalberktas solutionmethodologiesfordebrisremovalindisasterresponse AT baharyetiskara solutionmethodologiesfordebrisremovalindisasterresponse AT oyaekinkarasan solutionmethodologiesfordebrisremovalindisasterresponse
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Solution methodologies for debris removal in disaster response

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