Monte Carlo Algorithms for the Detection of Necessary Linear Matrix Inequality Constraints

Shafiu Jibrin, Irwin S. Pressman

Research output: Contribution to journalArticle

5 Scopus citations


We reduce the size of large semidefinite programming problems by identifying necessary linear matrix inequalities (LMI's) using Monte Carlo techniques. We describe three algorithms for detecting necessary LMI constraints that extend algorithms used in linear programming to semidefinite programming. We demonstrate that they are beneficial and could serve as tools for a semidefinite programming preprocessor.

Original languageEnglish (US)
Pages (from-to)139-153
Number of pages15
JournalInternational Journal of Nonlinear Sciences and Numerical Simulation
Issue number2
StatePublished - 2001


ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • Computational Mechanics
  • Mechanics of Materials
  • Applied Mathematics
  • Modeling and Simulation
  • Physics and Astronomy(all)
  • Statistical and Nonlinear Physics

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