Demand Management in Evacuation: Models, Algorithms, and Applications

dc.contributor.authorBish, Douglas R.en
dc.contributor.committeecochairHobeika, Antoine G.en
dc.contributor.committeecochairSherali, Hanif D.en
dc.contributor.committeememberKachroo, Pushkinen
dc.contributor.committeememberTrani, Antonio A.en
dc.contributor.committeememberBaik, Hojongen
dc.contributor.departmentCivil Engineeringen
dc.date.accessioned2014-03-14T20:14:41Zen
dc.date.adate2006-08-15en
dc.date.available2014-03-14T20:14:41Zen
dc.date.issued2006-07-31en
dc.date.rdate2010-10-12en
dc.date.sdate2006-08-03en
dc.description.abstractEvacuation planning is an important disaster management tool. A large-scale evacuation of a region by automobile is a difficult task, especially as demand is often greater than supply. This is made more difficult as the imbalance of supply and demand actually reduces supply due to congestion. Currently, most of the emphasis in evacuation planning is on supply management. The purpose of this dissertation is to introduce and study sophisticated demand management tools, specifically, staging and routing of evacuees. These tools can be used to produce evacuation strategies that reduce or eliminate congestion. A strategic planning model is introduced that accounts for evacuation dynamics and the non-linearities in travel times associated with congestion, yet is tractable and can be applied to large-scale networks. Objective functions of potential interest in evacuation planning are introduced and studied in the context of this model. Insights into the use of staging and routing in evacuation management are delineated and solution techniques are developed. Two different strategic approaches are studied in the context of this model. The first strategic approach is to control the evacuation at a disaggregate level, where customized staging and routing plans are produced for each individual or family unit. The second strategic approach is to control the evacuation at a more aggregate level, where evacuation plans are developed for a larger group of evacuees, based on pre-defined geographic areas. In both approaches, shelter requirements and preferences can also be considered. Computational experience using these two strategic approaches, and their respective solution techniques, is provided using a real network pertaining to Virginia Beach, Virginia, in order to demonstrate the efficacy of the proposed methodologies.en
dc.description.degreePh. D.en
dc.identifier.otheretd-08032006-135013en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08032006-135013/en
dc.identifier.urihttp://hdl.handle.net/10919/28501en
dc.publisherVirginia Techen
dc.relation.haspartETD_Dissertation2.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectstagingen
dc.subjectroutingen
dc.subjectmixed-integer programmingen
dc.subjectdemand managementen
dc.subjectevacuation managementen
dc.titleDemand Management in Evacuation: Models, Algorithms, and Applicationsen
dc.typeDissertationen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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