Artículo

A note on the McCormick second-order constraint qualification

Fazzio, Nadia Soledad Icon; Sanchez, María Daniela Icon; Schuverdt, María Laura Icon

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Fecha

12/2022

Editorial

Brazilian Society of Applied and Computational Mathematics

Revista

Trends in Computational and Applied Mathematics

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ISSN

2676-0029

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Inglés

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Resumen

The study of optimality conditions and constraint qualification is a key  topic in nonlinear optimization. In this work, we present a reformulation of the well-known second-order constraint qualification described by McCormick in [17]. This reformulation is based on the use of feasible arcs, but is independent of Lagrange multipliers. Using such a reformulation, we can show that a local minimizer verifies the strong second-order necessary optimality condition. We can also prove that the reformulation is weaker than the known relaxed constant rank constraint qualification in [19]. Furthermore, we demonstrate that the condition is neither related to the MFCQ+WCR in [8] nor to the CCP2 condition, the companion constraint qualification associated with the second-order sequential optimality condition AKKT2 in [5].

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