- Title
- Relaxed Lagrangian duality in convex infinite optimization: Reverse strong duality and optimality
- Creator
- Dinh, Nguyen; Goberna, Miguel; Lopez, Marco; Volle, Michel
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/192044
- Identifier
- vital:17924
- Identifier
-
https://doi.org/10.48550/arxiv.2106.09299
- Identifier
- ISSN:2562-5527
- Abstract
- We associate with each convex optimization problem posed on some locally convex space with an infinite index set T, and a given non-empty family H formed by finite subsets of T, a suitable Lagrangian-Haar dual problem. We provide reverse H-strong duality theorems, H-Farkas type lemmas and optimality theorems. Special attention is addressed to infinite and semi-infinite linear optimization problems.
- Publisher
- Biemdas Academic Publishers
- Relation
- Journal of Applied and Numerical Optimization Vol. , no. (2021), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright authors
- Subject
- Mathematics - Optimization and Control; 4903 Numerical and computational mathematics; 4901 Applied mathematics
- Reviewed
- Funder
- This research was supported by Vietnam National University HoChiMinh city (VNUHCM) under the grant number B2021-28-03 (N. Dinh) and by Ministerio de Ciencia, Innovaci´on y Universidades (MCIU), Agencia Estatal de Investigaci´on (AEI), and European Regional Development Fund (ERDF), Project PGC2018-097960-B-C22 (M.A. Goberna and M.A. L´opez
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