- Title
- A unifying approach to robust convex infinite optimization duality
- Creator
- Dinh, Nguyen; Goberna, Miguel; López, Marco; Volle, Michel
- Date
- 2017
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/165204
- Identifier
- vital:13210
- Identifier
-
https://doi.org/10.1007/s10957-017-1136-x
- Identifier
- ISBN:0022-3239
- Abstract
- This paper considers an uncertain convex optimization problem, posed in a locally convex decision space with an arbitrary number of uncertain constraints. To this problem, where the uncertainty only affects the constraints, we associate a robust (pessimistic) counterpart and several dual problems. The paper provides corresponding dual variational principles for the robust counterpart in terms of the closed convexity of different associated cones.
- Publisher
- Springer New York LLC
- Relation
- Journal of Optimization Theory and Applications Vol. 174, no. 3 (2017), p. 650-685; http://purl.org/au-research/grants/arc/DP160100854
- Rights
- Copyright © 2017, Springer Science+Business Media, LLC.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; 0906 Electrical and Electronic Engineering; Robust convex optimization; Lagrange duality; Strong duality; Robust strong duality; Uniform robust strong duality; Robust reverse strong duality
- Full Text
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