Feasible interior methods using slacks for nonlinear optimization

Richard H. Byrd*, Jorge Nocedal, Richard A. Waltz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

A slack-based feasible interior point method is described which can be derived as a modification of infeasible methods. The modification is minor for most line search methods, but trust region methods require special attention. It is shown how the Cauchy point, which is often computed in trust region methods, must be modified so that the feasible method is effective for problems containing both equality and inequality constraints. The relationship between slack-based methods and traditional feasible methods is discussed. Numerical results using the KNITRO package show the relative performance of feasible versus infeasible interior point methods.

Original languageEnglish (US)
Pages (from-to)35-61
Number of pages27
JournalComputational Optimization and Applications
Volume26
Issue number1
DOIs
StatePublished - Oct 2003

Keywords

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

ASJC Scopus subject areas

  • Control and Optimization
  • Computational Mathematics
  • Applied Mathematics

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