SDPLIB

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 58 articles , 1 standard article )

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  1. Henrion, Didier; Naldi, Simone; Safey El Din, Mohab: SPECTRA -- a Maple library for solving linear matrix inequalities in exact arithmetic (2019)
  2. Fathi-Hafshejani, S.; Fakharzadeh Jahromi, A.; Peyghami, M. Reza: A unified complexity analysis of interior point methods for semidefinite problems based on trigonometric kernel functions (2018)
  3. Raghunathan, Arvind U.; Biegler, Lorenz T.: (LDL^T) direction interior point method for semidefinite programming (2018)
  4. Zhang, Richard Y.; White, Jacob K.: GMRES-accelerated ADMM for quadratic objectives (2018)
  5. Yang, Ximei; Liu, Hongwei; Zhang, Yinkui: An arc-search infeasible-interior-point method for symmetric optimization in a wide neighborhood of the central path (2017)
  6. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  7. Ling, Aifan: An inexact non-interior continuation method for semidefinite programming: convergence analysis and numerical results (2016)
  8. Nayak, Rupaj Kumar; Desai, Jitamitra: A modified homogeneous potential reduction algorithm for solving the monotone semidefinite linear complementarity problem (2016)
  9. 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)
  10. Jibrin, Shafiu; Swift, James W.: Constraint consensus methods for finding strictly feasible points of linear matrix inequalities (2015)
  11. Kakihara, Satoshi; Ohara, Atsumi; Tsuchiya, Takashi: Curvature integrals and iteration complexities in SDP and symmetric cone programs (2014)
  12. Yang, Ximei; Liu, Hongwei; Dong, Xiaoliang: Polynomial convergence of Mehrotra-type prediction-corrector infeasible-IPM for symmetric optimization based on the commutative class directions (2014)
  13. Jan Fiala, Michal Kocvara, Michael Stingl: PENLAB: A MATLAB solver for nonlinear semidefinite optimization (2013) arXiv
  14. Kim, Sunyoung; Kojima, Masakazu: Exploiting sparsity in SDP relaxation of polynomial optimization problems (2012)
  15. Machacek, John; Jibrin, Shafiu: An interior point method for solving semidefinite programs using cutting planes and weighted analytic centers (2012)
  16. 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)
  17. Yamashita, Hiroshi; Yabe, Hiroshi; Harada, Kouhei: A primal-dual interior point method for nonlinear semidefinite programming (2012)
  18. Yamashita, Makoto; Fujisawa, Katsuki; Fukuda, Mituhiro; Kobayashi, Kazuhiro; Nakata, Kazuhide; Nakata, Maho: Latest developments in the SDPA family for solving large-scale SDPs (2012)
  19. Kim, Sunyoung; Kojima, Masakazu; Mevissen, Martin; Yamashita, Makoto: Exploiting sparsity in linear and nonlinear matrix inequalities via positive semidefinite matrix completion (2011)
  20. Andersen, Martin S.; Dahl, Joachim; Vandenberghe, Lieven: Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones (2010)

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