SDPNAL

SDPNAL version 0.1 -- a MATLAB software for semidefinite programming based on a semi-smooth Newton-CG augmented Lagrangian method. Important note: this is a research software. It is not intended nor designed to be a general purpose software at the moment. The solver is expected to be robust if the primal and dual SDPs are both non-degenerate at the optimal solutions. However, if either of one of them is degenerate, then the solver may not be able to solve the SDPs accurately. This software package is designed for solving standard SDP problems with max{n1,...,nN} (nk=dimension of matrix variable Xk) up to 2000. The number of linear equality constraints (dimension of b) can be large. In our numerical experiments, we have successfully solved SDPs with m > 1 million.

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References in zbMATH (referenced in 6 articles )

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  1. Ahmadi, Amir Ali; Majumdar, Anirudha: DSOS and SDSOS optimization: more tractable alternatives to sum of squares and semidefinite optimization (2019)
  2. Ghasemi, M.; Lasserre, J. B.; Marshall, M.: Lower bounds on the global minimum of a polynomial (2014)
  3. Monteiro, Renato D. C.; Ortiz, Camilo; Svaiter, Benar F.: A first-order block-decomposition method for solving two-easy-block structured semidefinite programs (2014)
  4. Wang, Li; Guo, Feng: Semidefinite relaxations for semi-infinite polynomial programming (2014)
  5. Nie, Jiawang; Wang, Li: Regularization methods for SDP relaxations in large-scale polynomial optimization (2012)
  6. Wen, Zaiwen; Goldfarb, Donald; Yin, Wotao: Alternating direction augmented Lagrangian methods for semidefinite programming (2010)