SEQUENTIAL QUADRATIC PROGRAMMING METHODS FOR NONLINEAR PROGRAMMING.

Philip E. Gill, Walter Murray, Michael A. Saunders, Margaret H. Wright

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sequential quadratic programming (SQP) methods are among the most effective techniques known today for solving nonlinearly constrained optimization problems. This paper presents an overview of SQP methods based on a quasi-Newton approximation to the Hessian of the Lagrangian function (or an augmented Lagrangian function). We briefly describe some of the issues in the formulation of SQP methods, including the form of the subproblem and the choice of merit function. We conclude with a list of available SQP software.

Original languageEnglish (US)
Title of host publicationNATO ASI Series, Series F
Subtitle of host publicationComputer and Systems Sciences
PublisherSpringer Verlag
Pages679-700
Number of pages22
ISBN (Print)3540128875, 9783540128878
DOIs
StatePublished - 1984

Publication series

NameNATO ASI Series, Series F: Computer and Systems Sciences
Volume9

ASJC Scopus subject areas

  • Engineering(all)

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