Solving semidefinite-quadratic-linear programs using SDPT3

Mathematical Programming volume 95, pages189–217(2003)Cite this article

Abstract.

 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.

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Affiliations

  1. Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. e-mail: reha@andrew.cmu.edu. Research supported in part by NSF through grant CCR-9875559., US

    R. H. Tütüncü

  2. Department of Mathematics, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260. e-mail: mattohkc@math.nus.edu.sg. Research supported in part by the Singapore-MIT Alliance., SG

    K. C. Toh

  3. School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York 14853, USA. e-mail: miketodd@cs.cornell.edu. Research supported in part by NSF through grant DMS-9805602 and ONR through grant N00014-96-1-0050., US

    M. J. Todd

Authors
  1. R. H. Tütüncü
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  2. K. C. Toh
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  3. M. J. Todd
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Additional information

Received: March 19, 2001 / Accepted: January 18, 2002 Published online: October 9, 2002

Mathematics Subject Classification (2000): 90C05, 90C22

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Tütüncü, R., Toh, K. & Todd, M. Solving semidefinite-quadratic-linear programs using SDPT3. Math. Program., Ser. B 95, 189–217 (2003). https://doi.org/10.1007/s10107-002-0347-5

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Keywords

  • Computational Result
  • Test Problem
  • Computational Experiment
  • Search Direction
  • Implementation Detail