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dc.contributor.advisorMiller-Hooks, Eliseen_US
dc.contributor.authorFeng, Leien_US
dc.date.accessioned2014-02-06T06:30:37Z
dc.date.available2014-02-06T06:30:37Z
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1903/14829
dc.description.abstractThere are a variety of circumstances in which large numbers of people gather and must disperse. These include, for example, carnivals, parades, and other situations involving entrance to or exit from complex buildings, sport stadiums, commercial malls, and other type of facilities. Under these situations, people move on foot, commonly, in groups. Other circumstances related to large crowds involve high volumes of people waiting at transportation stations, airports, and other types of high traffic generation points. In these cases, a myriad of people need to be transported by bus, train, or other vehicles. The phenomenon of moving in groups also arises in these vehicular traffic scenarios. For example, groups may travel together by carpooling or ridesharing as a cost-saving measure. The movement of significant numbers of people by automobile also occurs in emergency situations, such as transporting large numbers of carless and mobility-impaired persons from the impacted area to shelters during evacuation of an urban area. This dissertation addresses four optimization problems on the design of facilities and/or operations to support efficient movement of large numbers of people who travel in groups. A variety of modeling approaches, including bi-level and nonlinear programming are applied to formulate the identified problems. These formulations capture the complexity and diverse characteristics that arise from, for example, grouping behavior, interactions in decisions by the system and its users, inconvenience constraints for passengers, and interdependence of strategic and operational decisions. These models aim to provide: (1) estimates of how individuals and groups distribute themselves over the network in crowd situations; (2) an optimal configuration of the physical layout to support large crowd movement; (3) an efficient fleet resource management tool for ridesharing services; and (4) tools for effective regional disaster planning. A variety of solution algorithms, including a meta-heuristic scheme seeking a pure-strategy Nash equilibrium, a multi-start tabu search with sequential quadratic programming procedure, and constraint programming based column generation are developed to solve the formulated problems. All developed models and solution methodologies were employed on real-world or carefully created fictitious examples to demonstrate their effectiveness.en_US
dc.language.isoenen_US
dc.titleEfficient People Movement through Optimal Facility Configuration and Operationen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentCivil Engineeringen_US
dc.subject.pqcontrolledCivil engineeringen_US
dc.subject.pqcontrolledOperations researchen_US
dc.subject.pqcontrolledTransportation planningen_US
dc.subject.pquncontrolledEvaucationen_US
dc.subject.pquncontrolledLocation-Routingen_US
dc.subject.pquncontrolledOptimizationen_US
dc.subject.pquncontrolledPlanningen_US
dc.subject.pquncontrolledVehicle Routingen_US


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