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A minimal face constant rank constraint qualification for reducible conic programming

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Autor(es):
Andreani, Roberto ; Haeser, Gabriel ; Mito, Leonardo M. ; Ramirez, Hector
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: MATHEMATICAL PROGRAMMING; v. N/A, p. 27-pg., 2025-05-24.
Resumo

In a previous paper [Andreani et al, Math. Prog. 202, p. 473-514, 2023] we introduced a constant rank constraint qualification for nonlinear semidefinite and second-order cone programming by considering all faces of the underlying cone. This condition is independent of Robinson's condition and it implies a strong second-order necessary optimality condition which depends on a single Lagrange multiplier instead of the full set of Lagrange multipliers. In this paper we expand on this result in several directions, namely, we consider the larger class of C2-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {C}<^>2-$$\end{document}cone reducible constraints and we show that it is not necessary to consider all faces of the cone; instead a single specific face should be considered (which turns out to be weaker than Robinson's condition) in order for the first order necessary optimality condition to hold. This gives rise to a notion of facial reduction for nonlinear conic programming, that allows locally redefining the original problem only in terms of this specific face instead of the whole cone, providing a more robust formulation of the problem in which Robinson's condition holds. We were also able to prove the strong second-order necessary optimality condition in this context by considering only the subfaces of this particular face, which is a new result even in nonlinear programming. (AU)

Processo FAPESP: 17/17840-2 - Estimativas de erro em otimização não linear
Beneficiário:Leonardo Makoto Mito
Modalidade de apoio: Bolsas no Brasil - Doutorado
Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
Beneficiário:Francisco Louzada Neto
Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
Processo FAPESP: 17/18308-2 - Condições de otimalidade e algoritmos de segunda-ordem
Beneficiário:Gabriel Haeser
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 23/08706-1 - Métodos computacionais de otimização
Beneficiário:Ernesto Julián Goldberg Birgin
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 18/24293-0 - Métodos computacionais de otimização
Beneficiário:Sandra Augusta Santos
Modalidade de apoio: Auxílio à Pesquisa - Temático