An interior point algorithm for large-scale nonlinear programming

Richard H. Byrd*, Mary E. Hribar, Jorge Nocedal

*Corresponding author for this work

Research output: Contribution to journalArticle

880 Scopus citations

Abstract

The design and implementation of a new algorithm for solving large nonlinear programming problems is described. It follows a barrier approach that employs sequential quadratic programming and trust regions to solve the subproblems occurring in the iteration. Both primal and primal-dual versions of the algorithm are developed, and their performance is illustrated in a set of numerical tests.

Original languageEnglish (US)
Pages (from-to)877-900
Number of pages24
JournalSIAM Journal on Optimization
Volume9
Issue number4
DOIs
StatePublished - Sep 1999

Keywords

  • Barrier method
  • Constrained optimization
  • Interior point method
  • Large-scale optimization
  • Nonlinear programming
  • Primal method
  • Primal-dual method
  • Sequential quadratic programming
  • Trust region method

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'An interior point algorithm for large-scale nonlinear programming'. Together they form a unique fingerprint.

  • Cite this