dc.contributor.author Demange, Marc dc.contributor.author Gabrel, Virginie dc.contributor.author Haddad, Marcel Adonis dc.contributor.author Murat, Cécile dc.date.accessioned 2020-07-01T11:27:31Z dc.date.available 2020-07-01T11:27:31Z dc.date.issued 2020 dc.identifier.uri https://basepub.dauphine.fr/handle/123456789/20902 dc.language.iso en en dc.subject p-Center en dc.subject shelters en dc.subject wildfires en dc.subject.ddc 005 en dc.title A robust p-Center Problem under Pressure to locate Shelters in Wildfire Context en dc.type Document de travail / Working paper dc.description.abstracten The location of shelters in different areas threatened by wildfires is one of the possible ways to reduce fatalities in a context of an increasing number of catastrophic and severe wildfires. These shelters will enable the population in the area to be protected in case of fire outbreaks. The subject of our study is to determine the best place for shelters in a given territory. The territory, divided into zones, is represented by a graph in which eachzone corresponds to a node and two nodes are linked by an edge if it is feasible to go directly from one zone to the other. The problem is to locate p shelters on nodes so that the maximum distance of any node to its nearest shelter is minimized. When the uncertainty of fire outbreaks is not considered, this problem corresponds to the well-known p-Center problem on a graph. In this article, the uncertainty of fire outbreaks is introduced taking into account a finite set of fire scenarios. A scenario defines a fire outbreak on a single zone with the main consequence of modifying evacuation paths. Several evacuation paths may become impracticable and the ensuing evacuation decisions made under pressure may no longer be rational. In this context, the new issue under consideration is to place p shelters on a graph so that the maximum evacuation distance of any node to its nearest shelter in any scenario is minimized. We refer to this problem as the Robust p-Center problem under Pressure. After proving the NP-hardness of this problem on subgraphs of grids, we propose a first formulation based on 0-1 Linear Programming. For real size instances, the sizes of the 0-1 Linear Programs are huge and we propose a decomposition scheme to solve them exactly. Experimental results outline the efficiency of our approach. en dc.publisher.city Paris en dc.relation.ispartofseriestitle Preprint Lamsade en dc.identifier.urlsite https://hal.archives-ouvertes.fr/hal-02749732 en dc.subject.ddclabel Programmation, logiciels, organisation des données en dc.description.ssrncandidate non en dc.description.halcandidate non en dc.description.readership recherche en dc.description.audience International en dc.date.updated 2020-07-01T11:23:15Z hal.person.labIds hal.person.labIds 989 hal.person.labIds 989 hal.person.labIds 989
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