Dual-Based Local Search for Deterministic, Stochastic and Robust Variants of the Connected Facility Location Problem

dc.contributor.advisorRaghavan, Subramanianen_US
dc.contributor.authorBardossy, Maria G.en_US
dc.contributor.departmentBusiness and Management: Decision & Information Technologiesen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2011-10-08T06:40:53Z
dc.date.available2011-10-08T06:40:53Z
dc.date.issued2011en_US
dc.description.abstractIn this dissertation, we propose the study of a family of network design problems that arise in a wide range of practical settings ranging from telecommunications to data management. We investigate the use of heuristic search procedures coupled with lower bounding mechanisms to obtain high quality solutions for deterministic, stochastic and robust variants of these problems. We extend the use of well-known methods such as the sample average approximation for stochastic optimization and the Bertsimas and Sim approach for robust optimization with heuristics and lower bounding mechanisms. This is particular important for NP-complete problems where even deterministic and small instances are difficult to solve to optimality. Our extensions provide a novel way of applying these techniques while using heuristics; which from a practical perspective increases their usefulness.en_US
dc.identifier.urihttp://hdl.handle.net/1903/12088
dc.subject.pqcontrolledOperations researchen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pqcontrolledManagementen_US
dc.subject.pquncontrolledconnected facility locationen_US
dc.subject.pquncontrolleddual-ascenten_US
dc.subject.pquncontrolledlocal searchen_US
dc.subject.pquncontrollednetwork designen_US
dc.subject.pquncontrolledrobust optimizationen_US
dc.subject.pquncontrolledsample average approximationen_US
dc.titleDual-Based Local Search for Deterministic, Stochastic and Robust Variants of the Connected Facility Location Problemen_US
dc.typeDissertationen_US

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