DSDP5
Algorithm 875: DSDP5--software for semidefinite programming. DSDP implements the dual-scaling algorithm for semidefinite programming. The source code for this interior-point algorithm, written entirely in ANSI C, is freely available under an open source license. The solver can be used as a subroutine library, as a function within the Matlab environment, or as an executable that reads and writes to data files. Initiated in 1997, DSDP has developed into an efficient and robust general-purpose solver for semidefinite programming. Its features include a convergence proof with polynomially bounded worst-case complexity, primal and dual feasible solutions when they exist, certificates of infeasibility when solutions do not exist, initial points that can be feasible or infeasible, relatively low memory requirements for an interior-point method, sparse and low-rank data structures, extensibility that allows applications to customize the solver and improve its performance, a subroutine library that enables it to be linked to larger applications, scalable performance for large problems on parallel architectures, and a well-documented interface and examples of its use. The package has been used in many applications and tested for efficiency, robustness, and ease of use.
(Source: http://dl.acm.org/)
This software is also peer reviewed by journal TOMS.
This software is also peer reviewed by journal TOMS.
Keywords for this software
References in zbMATH (referenced in 26 articles , 1 standard article )
Showing results 1 to 20 of 26.
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- Grippo, Luigi; Palagi, Laura; Piccialli, Veronica: An unconstrained minimization method for solving low-rank SDP relaxations of the maxcut problem (2011)
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- Kleniati, P. M.; Parpas, P.; Rustem, B.: Decomposition-based method for sparse semidefinite relaxations of polynomial optimization problems (2010)
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