Mathematical Programming

, Volume 95, Issue 2, pp 189–217 | Cite as

Solving semidefinite-quadratic-linear programs using SDPT3

  • R. H. Tütüncü
  • K. C. Toh
  • M. J. Todd


 This paper discusses computational experiments with linear optimization problems involving semidefinite, quadratic, and linear cone constraints (SQLPs). Many test problems of this type are solved using a new release of SDPT3, a Matlab implementation of infeasible primal-dual path-following algorithms. The software developed by the authors uses Mehrotra-type predictor-corrector variants of interior-point methods and two types of search directions: the HKM and NT directions. A discussion of implementation details is provided and computational results on problems from the SDPLIB and DIMACS Challenge collections are reported.


Computational Result Test Problem Computational Experiment Search Direction Implementation Detail 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • R. H. Tütüncü
    • 1
  • K. C. Toh
    • 2
  • M. J. Todd
    • 3
  1. 1.Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. e-mail: Research supported in part by NSF through grant CCR-9875559.US
  2. 2.Department of Mathematics, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260. e-mail: Research supported in part by the Singapore-MIT Alliance.SG
  3. 3.School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York 14853, USA. e-mail: Research supported in part by NSF through grant DMS-9805602 and ONR through grant N00014-96-1-0050.US

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