CSDP, A C Library for Semidefinite Programming. This is the project page for the CSDP project of COIN-OR. CSDP is a library of routines that implements a predictor corrector variant of the semidefinite programming algorithm of Helmberg, Rendl, Vanderbei, and Wolkowicz. The main advantages of this code are that it is written to be used as a callable subroutine, it is written in C for efficiency, the code runs in parallel on shared memory multi-processor systems, and it makes effective use of sparsity in the constraint matrices. CSDP has been compiled on many different systems. The code should work on any system with an ANSI C Compiler and BLAS/LAPACK libraries.

References in zbMATH (referenced in 176 articles , 2 standard articles )

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  1. Elloumi, Sourour; Lambert, Amélie: Global solution of non-convex quadratically constrained quadratic programs (2019)
  2. Liuzzi, G.; Locatelli, M.; Piccialli, Veronica: A new branch-and-bound algorithm for standard quadratic programming problems (2019)
  3. Behrends, Sönke; Hübner, Ruth; Schöbel, Anita: Norm bounds and underestimators for unconstrained polynomial integer minimization (2018)
  4. Roux, Pierre; Voronin, Yuen-Lam; Sankaranarayanan, Sriram: Validating numerical semidefinite programming solvers for polynomial invariants (2018)
  5. Adjé, Assalé; Garoche, Pierre-Loïc; Magron, Victor: A sums-of-squares extension of policy iterations (2017)
  6. Arima, Naohiko; Kim, Sunyoung; Kojima, Masakazu; Toh, Kim-Chuan: A robust Lagrangian-DNN method for a class of quadratic optimization problems (2017)
  7. Billionnet, Alain; Elloumi, Sourour; Lambert, Amélie; Wiegele, Angelika: Using a conic bundle method to accelerate both phases of a quadratic convex reformulation (2017)
  8. Garraffa, Michele; Della Croce, Federico; Salassa, Fabio: An exact semidefinite programming approach for the max-mean dispersion problem (2017)
  9. Gethner, Ellen; Hogben, Leslie; Lidický, Bernard; Pfender, Florian; Ruiz, Amanda; Young, Michael: On crossing numbers of complete tripartite and balanced complete multipartite graphs (2017)
  10. Papp, Dávid: Semi-infinite programming using high-degree polynomial interpolants and semidefinite programming (2017)
  11. Adasme, Pablo; Lisser, Abdel: A computational study for bilevel quadratic programs using semidefinite relaxations (2016)
  12. Billionnet, Alain; Elloumi, Sourour; Lambert, Amélie: Exact quadratic convex reformulations of mixed-integer quadratically constrained problems (2016)
  13. Buchheim, Christoph; Montenegro, Maribel; Wiegele, Angelika: A coordinate ascent method for solving semidefinite relaxations of non-convex quadratic integer programs (2016)
  14. Bugarin, Florian; Henrion, Didier; Lasserre, Jean Bernard: Minimizing the sum of many rational functions (2016)
  15. Dong, Hongbo: Relaxing nonconvex quadratic functions by multiple adaptive diagonal perturbations (2016)
  16. Elloumi, Sourour; Lambert, Amélie: Comparison of quadratic convex reformulations to solve the Quadratic Assignment problem (2016)
  17. Glebov, Roman; Král’, Daniel; Volec, Jan: A problem of Erd\Hosand Sós on 3-graphs (2016)
  18. Kim, Sunyoung; Kojima, Masakazu; Toh, Kim-Chuan: A Lagrangian-DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems (2016)
  19. Krislock, Nathan; Malick, Jér^ome; Roupin, Frédéric: Computational results of a semidefinite branch-and-bound algorithm for $k$-cluster (2016)
  20. Létocart, Lucas; Wiegele, Angelika: Exact solution methods for the $k$-item quadratic knapsack problem (2016)

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