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    Characterizations of robust solution set of convex programs with uncertain data

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    Authors
    Li, X.
    Wang, Song
    Date
    2017
    Type
    Journal Article
    
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    Citation
    Li, X. and Wang, S. 2017. Characterizations of robust solution set of convex programs with uncertain data. Optimization Letters: pp. 1-16.
    Source Title
    Optimization Letters
    DOI
    10.1007/s11590-017-1187-9
    ISSN
    1862-4472
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/62847
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 Springer-Verlag GmbH Germany In this paper, we study convex programming problems with data uncertainty in both the objective function and the constraints. Under the framework of robust optimization, we employ a robust regularity condition, which is much weaker than the ones in the open literature, to establish various properties and characterizations of the set of all robust optimal solutions of the problems. These are expressed in term of subgradients, Lagrange multipliers and epigraphs of conjugate functions. We also present illustrative examples to show the significances of our theoretical results.

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