An SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility in the original problem and the QP subproblems is discussed.Expand

This ebook Practical Optimization by Philip E. Gill is presented in pdf format and the full version of this ebook in DjVu, ePub, doc, txt, PDF forms is presented.Expand

An SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility in the original problem and the QP subproblems is discussed and a reduced-Hessian semidefinite QP solver (SQOPT) is discussed.Expand

The methods are intimately based on the recurrence of matrix factorizations and are linked to earlier work on quasi-Newton methods and quadratic programming.Expand

A multisectional support useful as a trellis and for other purposes. Each section includes one or more components to which the corresponding components of super- and/or subjacent sections can be… Expand

This paper describes a modification to the Gauss–Newton method for the solution of nonlinear least-squares problems. The new method seeks to avoid the deficiencies in the Gauss–Newton method by… Expand

This report forms the user's guide for Version 4.0 of NPSOL, a set of Fortran subroutines designed to minimize a smooth function subject to constraints, which may include simple bounds on the… Expand

This work reviews classical barrier-function methods for nonlinear programming based on applying a logarithmic transformation to inequality constraints and shows a “projected Newton barrier” method to be equivalent to Karmarkar's projective method for a particular choice of the barrier parameter.Expand

SNOPT minimizes a linear or nonlinear function subject to bounds on the variables and sparse linear orNonlinear constraints and is suitable for large-scale linear and quadratic programming and for linearly constrained optimization, as well as for general nonlinear programs.Expand