A Note on the McCormick Second-Order Constraint Qualification
AUTOR(ES)
FAZZIO, N. S.; NCHEZ, M. D. SÁ; SCHUVERDT, M. L.
FONTE
Trends in Computational and Applied Mathematics
DATA DE PUBLICAÇÃO
2022
RESUMO
ABSTRACT 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 AKKT 2 in 5.
