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dc.contributor.authorBardossy, M. Gisela
dc.contributor.authorRaghavan, S.
dc.date.accessioned2017-05-09T16:16:15Z
dc.date.available2017-05-09T16:16:15Z
dc.date.issued2016
dc.description.abstractIn this paper we consider the Robust Connected Facility Location (ConFL) problem within the robust discrete optimization framework introduced by Bertsimas and Sim (2003). We propose an Approximate Robust Optimization (ARO) method that uses a heuristic and a lower bounding mechanism to rapidly find high-quality solutions. The use of a heuristic and a lower bounding mechanism–as opposed to solving the robust optimization (RO) problem exactly–within this ARO approach significantly decreases its computational time. This enables one to obtain high quality solutions to large-scale robust optimization problems and thus broadens the scope and applicability of robust optimization (from a computational perspective) to other NP-hard problems. Our computational results attest to the efficacy of the approach.en_US
dc.format.extent30 pagesen_US
dc.identifierdoi:10.13016/M2BG2B
dc.identifier.citationBardossy, M. G., & Raghavan, S. (2016). Approximate robust optimization for the Connected Facility Location problem. Discrete Applied Mathematics, 210(LAGOS'13: Seventh Latin-American Algorithms, Graphs, and Optimization Symposium, Playa del Carmen, Mexico - 2013), 246-260. doi:10.1016/j.dam.2015.10.011en_US
dc.identifier.urihttp://hdl.handle.net/11603/3902
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.isAvailableAtUniversity of Baltimore
dc.subjectnetwork designen_US
dc.subjectrobust optimizationen_US
dc.subjectheuristicsen_US
dc.subjectapproximationen_US
dc.subjectConnected Facility Location problemen_US
dc.titleApproximate Robust Optimization for the Connected Facility Location Problemen_US
dc.typeTexten_US


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