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Nguyen Dinh, Miguel A. Goberna, Marco A. López, Michel Volle, Relaxed Lagrangian duality in convex infinite optimization: Reverse strong duality and optimality

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DOI: 10.23952/jano.4.2022.1.02
Volume 4, Issue 1, 1 April 2022, Pages 3-18 

 

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.

 

How to Cite this Article:
Nguyen Dinh, Miguel A. Goberna, Marco A. López, Michel Volle, Relaxed Lagrangian duality in convex infinite optimization: Reverse strong duality and optimality, J. Appl. Numer. Optim. 4 (2022), 3-18.