On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

Andreas Wächter*, Lorenz T. Biegler

*Corresponding author for this work

Research output: Contribution to journalArticle

3684 Scopus citations

Abstract

We present a primal-dual interior-point algorithm with a filter line-search method for nonlinear programming. Local and global convergence properties of this method were analyzed in previous work. Here we provide a comprehensive description of the algorithm, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix. Heuristics are also considered that allow faster performance. This method has been implemented in the IPOPT code, which we demonstrate in a detailed numerical study based on 954 problems from the CUTEr test set. An evaluation is made of several line-search options, and a comparison is provided with two state-of-the-art interior-point codes for nonlinear programming.

Original languageEnglish (US)
Pages (from-to)25-57
Number of pages33
JournalMathematical Programming
Volume106
Issue number1
DOIs
StatePublished - May 1 2006

Keywords

  • Barrier method
  • Filter method
  • Interior-point method
  • Line search
  • Nonconvex constrained optimization
  • Nonlinear programming

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

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