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- W3166660250 abstract "We associate with each convex optimization problem, posed on some locally convex space, with infinitely many constraints indexed by the set T, and a given non-empty family H of finite subsets of T, a suitable Lagrangian-Haar dual problem. We obtain necessary and sufficient conditions for H-reducibility, that is, equivalence to some subproblem obtained by replacing the whole index set T by some element of H. Special attention is addressed to linear optimization, infinite and semi-infinite, and to convex problems with a countable family of constraints. Results on zero H-duality gap and on H-(stable) strong duality are provided. Examples are given along the paper to illustrate the meaning of the results." @default.
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- W3166660250 date "2022-02-07" @default.
- W3166660250 modified "2023-10-16" @default.
- W3166660250 title "Relaxed Lagrangian duality in convex infinite optimization: reducibility and strong duality" @default.
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- W3166660250 doi "https://doi.org/10.1080/02331934.2022.2031192" @default.
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