stabilized sqp – Optimization Online

A Globally Convergent Stabilized SQP Method: Superlinear Convergence

Published: 2014/07/01, Updated: 2014/07/08

Constrained Nonlinear Optimization augmented lagrangian method, nonlinear constraints, nonlinear programming, primal-dual algorithms, regularized methods, sequential quadratic programming, stabilized sqp

Regularized and stabilized sequential quadratic programming (SQP) methods are two classes of methods designed to resolve the numerical and theoretical difficulties associated with ill-posed or degenerate nonlinear optimization problems. Recently, a regularized SQP method has been proposed that allows convergence to points satisfying certain second-order KKT conditions (SIAM J. Optim., 23(4):1983–2010, 2013). The method is … Read more

SQP Methods for Parametric Nonlinear Optimization

Published: 2014/02/28, Updated: 2014/07/07

Moritz Diehl

Vyacheslav Kungurtsev

Nonlinear Optimization continuation methods, homotopy, model predictive control, nonlinear constraints, nonlinear programming, parametric nonlinear programming, sequential quadratic programming, stabilized sqp

Sequential quadratic programming (SQP) methods are known to be effi- cient for solving a series of related nonlinear optimization problems because of desirable hot and warm start properties–a solution for one problem is a good estimate of the solution of the next. However, standard SQP solvers contain elements to enforce global convergence that can interfere … Read more

A Regularized SQP Method with Convergence to Second-Order Optimal Points

Published: 2013/10/30, Updated: 2013/10/31

Philip E. Gill

Vyacheslav Kungurtsev

Daniel P. Robinson

Constrained Nonlinear Optimization, Nonlinear Optimization augmented lagrangian method, nonlinear programming, primal-dual algorithms, regularized methods, second-order optimality, sequential quadratic programming, stabilized sqp

Regularized and stabilized sequential quadratic programming methods are two classes of sequential quadratic programming (SQP) methods designed to resolve the numerical and theoretical difficulties associated with ill-posed or degenerate nonlinear optimization problems. Recently, a regularized SQP method has been proposed that provides a strong connection between augmented Lagrangian methods and stabilized SQP methods. The method … Read more

A GLOBALLY CONVERGENT STABILIZED SQP METHOD

Published: 2012/06/29

Philip E. Gill

Daniel P. Robinson

Sequential quadratic programming (SQP) methods are a popular class of methods for nonlinearly constrained optimization. They are particularly effective for solving a sequence of related problems, such as those arising in mixed-integer nonlinear programming and the optimization of functions subject to differential equation constraints. Recently, there has been considerable interest in the formulation of \emph{stabilized} … Read more