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An Augmented Lagrangian method for quasi-equilibrium problems

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Autor(es):
Bueno, L. F. ; Haeser, G. ; Lara, F. ; Rojas, F. N.
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: COMPUTATIONAL OPTIMIZATION AND APPLICATIONS; v. 76, n. 3, p. 30-pg., 2020-02-21.
Resumo

In this paper, we propose an Augmented Lagrangian algorithm for solving a general class of possible non-convex problems called quasi-equilibrium problems (QEPs). We define an Augmented Lagrangian bifunction associated with QEPs, introduce a secondary QEP as a measure of infeasibility and we discuss several special classes of QEPs within our theoretical framework. For obtaining global convergence under a new weak constraint qualification, we extend the notion of an Approximate Karush-Kuhn-Tucker (AKKT) point for QEPs (AKKT-QEP), showing that in general it is not necessarily satisfied at a solution, differently from its counterpart in optimization. We study some particular cases where AKKT-QEP does hold at a solution, while discussing the solvability of the subproblems of the algorithm. We also present illustrative numerical experiments. (AU)

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: 18/24293-0 - Métodos computacionais de otimização
Beneficiário:Sandra Augusta Santos
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 13/05475-7 - Métodos computacionais de otimização
Beneficiário:Sandra Augusta Santos
Modalidade de apoio: Auxílio à Pesquisa - Temático