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Please use this identifier to cite or link to this item: http://hdl.handle.net/1903/12088

Title: Dual-Based Local Search for Deterministic, Stochastic and Robust Variants of the Connected Facility Location Problem
Authors: Bardossy, Maria G.
Advisors: Raghavan, Subramanian
Department/Program: Business and Management: Decision & Information Technologies
Type: Dissertation
Sponsors: Digital Repository at the University of Maryland
University of Maryland (College Park, Md.)
Subjects: Operations research
Computer science
Management
Keywords: connected facility location
dual-ascent
local search
network design
robust optimization
sample average approximation
Issue Date: 2011
Abstract: In 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.
URI: http://hdl.handle.net/1903/12088
Appears in Collections:Decision, Operations & Information Technologies Theses and Dissertations
UMD Theses and Dissertations

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