On the implementation of an algorithm for large-scale equality constrained optimization

Marucha Lalee*, Jorge Nocedal, Todd Plantenga

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

92 Scopus citations


This paper describes a software implementation of Byrd and Omojokun's trust region algorithm for solving nonlinear equality constrained optimization problems. The code is designed for the efficient solution of large problems and provides the user with a variety of linear algebra techniques for solving the subproblems occurring in the algorithm. Second derivative information can be used, but when it is not available, limited memory quasi-Newton approximations are made. The performance of the code is studied using a set of difficult test problems from the CUTE collection.

Original languageEnglish (US)
Pages (from-to)682-706
Number of pages25
JournalSIAM Journal on Optimization
Issue number3
StatePublished - Aug 1998


  • Constrained optimization
  • Large-scale optimization
  • Minimization
  • Nonlinear optimization
  • Quasi-Newton methods
  • Trust region methods

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Applied Mathematics


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