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 67 articles , 1 standard article )

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  1. Jiang, Xin; Vandenberghe, Lieven: Bregman primal-dual first-order method and application to sparse semidefinite programming (2022)
  2. Souto, Mario; Garcia, Joaquim D.; Veiga, Álvaro: Exploiting low-rank structure in semidefinite programming by approximate operator splitting (2022)
  3. Garstka, Michael; Cannon, Mark; Goulart, Paul: COSMO: a conic operator splitting method for convex conic problems (2021)
  4. Kheirfam, Behrouz; Osmanpour, Naser; Keyanpour, Mohammad: An arc-search infeasible interior-point method for semidefinite optimization with the negative infinity neighborhood (2021)
  5. O’Donoghue, Brendan: Operator splitting for a homogeneous embedding of the linear complementarity problem (2021)
  6. Zhang, Richard Y.; Lavaei, Javad: Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion (2021)
  7. Zheng, Yang; Fantuzzi, Giovanni; Papachristodoulou, Antonis; Goulart, Paul; Wynn, Andrew: Chordal decomposition in operator-splitting methods for sparse semidefinite programs (2020)
  8. Banjac, Goran; Goulart, Paul; Stellato, Bartolomeo; Boyd, Stephen: Infeasibility detection in the alternating direction method of multipliers for convex optimization (2019)
  9. Yang, Ximei; Bai, Yanqin: An adaptive infeasible-interior-point method with the one-norm wide neighborhood for semi-definite programming (2019)
  10. 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)
  11. Raghunathan, Arvind U.; Biegler, Lorenz T.: (LDL^T) direction interior point method for semidefinite programming (2018)
  12. Zhang, Richard Y.; White, Jacob K.: GMRES-accelerated ADMM for quadratic objectives (2018)
  13. 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)
  14. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  15. Ling, Aifan: An inexact non-interior continuation method for semidefinite programming: convergence analysis and numerical results (2016)
  16. Nayak, Rupaj Kumar; Desai, Jitamitra: A modified homogeneous potential reduction algorithm for solving the monotone semidefinite linear complementarity problem (2016)
  17. 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)
  18. Jibrin, Shafiu; Swift, James W.: Constraint consensus methods for finding strictly feasible points of linear matrix inequalities (2015)
  19. Kakihara, Satoshi; Ohara, Atsumi; Tsuchiya, Takashi: Curvature integrals and iteration complexities in SDP and symmetric cone programs (2014)
  20. 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)

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