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Stabilized sequential quadratic programming: a survey
(Sociedade Brasileira de Pesquisa Operacional, 2014-11)
We review the motivation for, the current state-of-the-art in convergence results, and some open questions concerning the stabilized version of the sequential quadratic programming algorithm for constrained optimization. ...
Stabilized sequential quadratic programming: A survey
(Sociedade Brasileira de Pesquisa Operacional, 2014-09)
We review the motivation for, the current state-of-the-art in convergence results, and some open questions concerning the stabilized version of the sequential quadratic programming algorithm for constrained optimization. ...
On the cost of solving augmented Lagrangian subproblems
(Springer, 2020-07)
At each iteration of the augmented Lagrangian algorithm, a nonlinear subproblem is being solved. The number of inner iterations (of some/any method) needed to obtain a solution of the subproblem, or even a suitable approximate ...
A quasi-Newton strategy for the sSQP method for variational inequality and optimization problems
(Springer, 2013-02)
The quasi-Newton strategy presented in this paper preserves one of the most important features of the stabilized Sequential Quadratic Programming (sSQP) method, the local convergence without constraint qualifications ...
An inexact restoration strategy for the globalization of the sSQP method
(Springer, 2013-04)
A globally convergent algorithm based on the stabilized sequential quadratic programming (sSQP) method is presented in order to solve optimization problems with equality constraints and bounds. This formulation has ...
A computational tool for trend analysis and forecast of the COVID-19 pandemic
(Elsevier, 2021-03-10)
Purpose: This paper proposes a methodology and a computational tool to study the COVID-19 pandemic throughout the world and to perform a trend analysis to assess its local dynamics.
Methods: Mathematical functions are ...
TWO NEW WEAK CONSTRAINT QUALIFICATIONS AND APPLICATIONS
(SIAM PUBLICATIONSPHILADELPHIA, 2012)
We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients ...
Two new weak constraint qualifications and applications
(Society for Industrial and Applied Mathematics, 2012-01)
We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients ...