Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7673
Title: The Robust Network Loading Problem Under Hose Demand Uncertainty: Formulation, Polyhedral Analysis, and Computations
Authors: Altın, Ayşegül
Yaman, Hande
Pınar, Mustafa C.
Keywords: network loading problem
polyhedral demand uncertainty
hose model
robust optimization
polyhedral analysis
branch and cut
Issue Date: 2011
Publisher: Informs
Abstract: We consider the network loading problem (NLP) under a polyhedral uncertainty description of traffic demands. After giving a compact multicommodity flow formulation of the problem, we state a decomposition property obtained from projecting out the flow variables. This property considerably simplifies the resulting polyhedral analysis and computations by doing away with metric inequalities. Then we focus on a specific choice of the uncertainty description, called the "hose model," which specifies aggregate traffic upper bounds for selected endpoints of the network. We study the polyhedral aspects of the NLP under hose demand uncertainty and use the results as the basis of an efficient branch-and-cut algorithm. The results of extensive computational experiments on well-known network design instances are reported.
URI: https://doi.org/10.1287/ijoc.1100.0380
https://hdl.handle.net/20.500.11851/7673
ISSN: 1091-9856
1526-5528
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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