We consider nonlinear programs with inequality constraints, and we focus on the problem of
identifying those constraints which will be active at an isolated local solution. The correct …

Dieses Buch bietet eine umfassende und aktuelle Darstellung des Themenbereichs"
Numerische Lösung unrestringierter Optimierungsaufgaben mit differenzierbarer …

Transition to superlinear local convergence is shown for a modified version of the trust-
region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and …

A new algorithm for large-scale nonlinear programs with box constraints is introduced. The
algorithm is based on an efficient identification technique of the active set at the solution and …

In this paper we introduce a new exact augmented Lagrangian function for the solution of
general nonlinear programming problems. For this Lagrangian function a complete …

A sequential quadratic programming (SQP) method is presented that aims to overcome
some of the drawbacks of contemporary SQP methods. It avoids the difficulties associated …

In this paper, we propose a new QP-free method, which ensures the feasibility of all iterates,
for inequality constrained optimization. The method is based on a nonsmooth equation …

In this paper, we describe a two-stage method for solving optimization problems with bound
constraints. It combines the active-set estimate described in Facchinei and Lucidi (J Optim …

A method for the solution of minimization problems with simple bounds is presented. Global
convergence of a general scheme requiring the approximate solution of a single linear …

We present a sequential quadratic optimization (SQO) algorithm for nonlinear constrained
optimization. The method attains all of the strong global and fast local convergence …