Robust linear optimization under general norms

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چکیده

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Robust linear optimization under general norms

We propose a framework for robust modeling of linear programming problems using uncertainty sets described by an arbitrary norm. We explicitly characterize the robust counterpart as a convex optimization problem that involves the dual norm of the given norm. Under a Euclidean norm we recover the second order cone formulation in BenTal and Nemirovski [1, 2], El Ghaoui et al. [8, 9], while under ...

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ژورنال

عنوان ژورنال: Operations Research Letters

سال: 2004

ISSN: 0167-6377

DOI: 10.1016/j.orl.2003.12.007