File | |
language |
eng
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Author |
Lee, Gue Myung
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Description | Robust optimization problems, which have uncertain data, are considered. We prove surrogate duality theorems for robust quasiconvex optimization problems and surrogate min-max duality theorems for robust convex opti-mization problems. We give necessary and sufficient constraint qualifications for surrogate duality and surrogate min-max duality, and show some exam-ples at which such duality results are used effectively. Moreover, we obtain a surrogate duality theorem and a surrogate min-max duality theorem for semi-definite optimization problems in the face of data uncertainty.
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Subject | Nonlinear programming
quasiconvex programming
robust optimization
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Journal Title |
European Journal of Operational Research
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Volume | 231
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Issue | 2
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Start Page | 257
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End Page | 262
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ISSN | 03772217
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Published Date | 2013-12-01
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DOI | |
DOI Date | 2015-07-14
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NCID | AA0017802X
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NII Type |
Journal Article
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Format |
PDF
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Text Version |
著者版
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OAI-PMH Set |
Interdisciplinary Graduate School of Science and Engineering
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