SDPLIB 1. 2, a library of semidefinite programming test problems. SDLIB is a collection of semidefinite programming (SDP) test problems. The problems are drawn from a variety of applications, including truss topology design, control systems engineering, and relaxations of combinatorial optimization problems. The current version of the library contain a total of 92 SDP problems encoded in a standard format. It is hoped that SDPLIB will stimulate the development of improved software for the solution of SDP problems.

References in zbMATH (referenced in 51 articles , 1 standard article )

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  1. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  2. Ling, Aifan: An inexact non-interior continuation method for semidefinite programming: convergence analysis and numerical results (2016)
  3. Nayak, Rupaj Kumar; Desai, Jitamitra: A modified homogeneous potential reduction algorithm for solving the monotone semidefinite linear complementarity problem (2016)
  4. Yang, Ximei; Zhang, Yinkui; Liu, Hongwei; Pei, Yonggang: A Mizuno-Todd-Ye predictor-corrector infeasible-interior-point method for linear programming over symmetric cones (2016)
  5. Kakihara, Satoshi; Ohara, Atsumi; Tsuchiya, Takashi: Curvature integrals and iteration complexities in SDP and symmetric cone programs (2014)
  6. Jan Fiala, Michal Kocvara, Michael Stingl: PENLAB: A MATLAB solver for nonlinear semidefinite optimization (2013) arXiv
  7. Kim, Sunyoung; Kojima, Masakazu: Exploiting sparsity in SDP relaxation of polynomial optimization problems (2012)
  8. Machacek, John; Jibrin, Shafiu: An interior point method for solving semidefinite programs using cutting planes and weighted analytic centers (2012)
  9. Toh, Kim-Chuan; Todd, Michael J.; Tütüncü, Reha H.: On the implementation and usage of SDPT3 -- a Matlab software package for semidefinite-quadratic-linear programming, version 4.0 (2012)
  10. Yamashita, Hiroshi; Yabe, Hiroshi; Harada, Kouhei: A primal-dual interior point method for nonlinear semidefinite programming (2012)
  11. Yamashita, Makoto; Fujisawa, Katsuki; Fukuda, Mituhiro; Kobayashi, Kazuhiro; Nakata, Kazuhide; Nakata, Maho: Latest developments in the SDPA family for solving large-scale SDPs (2012)
  12. Kim, Sunyoung; Kojima, Masakazu; Mevissen, Martin; Yamashita, Makoto: Exploiting sparsity in linear and nonlinear matrix inequalities via positive semidefinite matrix completion (2011)
  13. Andersen, Martin S.; Dahl, Joachim; Vandenberghe, Lieven: Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones (2010)
  14. Caron, Richard J.; Traynor, Tim; Jibrin, Shafiu: Feasibility and constraint analysis of sets of linear matrix inequalities (2010)
  15. Ivanov, I.D.; de Klerk, E.: Parallel implementation of a semidefinite programming solver based on CSDP on a distributed memory cluster (2010)
  16. Kim, Sunyoung; Kojima, Masakazu: Solving polynomial least squares problems via semidefinite programming relaxations (2010)
  17. Rump, Siegfried M.: Verification methods: rigorous results using floating-point arithmetic (2010)
  18. Sivaramakrishnan, Kartik Krishnan: A parallel interior point decomposition algorithm for block angular semidefinite programs (2010)
  19. Wei, Hua; Wolkowicz, Henry: Generating and measuring instances of hard semidefinite programs (2010)
  20. de Klerk, Etienne; Sotirov, Renata: A new library of structured semidefinite programming instances (2009)

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