Interior methods for nonlinear optimization

Anders Forsgren, Philip E. Gill, Margaret H. Wright

Research output: Contribution to journalArticlepeer-review


Interior methods are an omnipresent, conspicuous feature of the constrained optimization landscape today, but it was not always so. Primarily in the form of barrier methods, interior-point techniques were popular during the 1960s for solving nonlinearly constrained problems. However, their use for linear programming was not even contemplated because of the total dominance of the simplex method. Vague but continuing anxiety about barrier methods eventually led to their abandonment in favor of newly emerging, apparently more efficient alternatives such as augmented Lagrangian and sequential quadratic programming methods. By the early 1980s, barrier methods were almost without exception regarded as a closed chapter in the history of optimization. This picture changed dramatically with Karmarkar's widely publicized announcement in 1984 of a fast polynomial-time interior method for linear programming; in 1985, a formal connection was established between his method and classical barrier methods. Since then, interior methods have advanced so far, so fast, that their influence has transformed both the theory and practice of constrained optimization. This article provides a condensed, selective look at classical material and recent research about interior methods for nonlinearly constrained optimization.

Original languageEnglish (US)
Pages (from-to)525-597
Number of pages73
JournalSIAM Review
Issue number4
StatePublished - Dec 2002


  • Barrier methods
  • Constrained minimization
  • Interior methods
  • Nonlinear constraints
  • Nonlinear programming
  • Penalty methods
  • Primal-dual methods

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Mathematics
  • Applied Mathematics


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