Relaxed Lagrangian duality in convex infinite optimization: reverse strong duality and optimality
Optimization and Control
2021-06-18 v1
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.
Cite
@article{arxiv.2106.09299,
title = {Relaxed Lagrangian duality in convex infinite optimization: reverse strong duality and optimality},
author = {Nguyen Dinh and Miguel A. Goberna and Marco A. Lopez and Michel Volle},
journal= {arXiv preprint arXiv:2106.09299},
year = {2021}
}
Comments
19 pages