Last revised July 29, 1997.
This page has been made frame-free for your viewing pleasure.
Comments and suggestions to madhu@cs.nyu.edu
Background Semidefinite Programming (SDP) is an extension to linear programming, where the goal is to minimize a linear objective function of a symmetric matrix subject to linear constraints on the matrix, and a cone constraint that requires the matrix to lie in the cone of positive semidefinite matrices. SDP has applications ranging from control theory to combinatorial optimization and optimal design of mechanical structures. Several exciting theoretical advances have been made in this field in the last five years or so. To learn more about SDP, check out the NEOS blurb and our collection of SDP resources, which includes links to other pages on SDP, a partial list of researchers, related meetings and conferences, journals, newsgroups, and FAQ's.
What is SDPpack?
SDPpack Version 0.9 beta runs under Matlab 5.0.
This version extends the previous release for semidefinite programming (SDP)
to mixed semidefinite-quadratic-linear programs (SQLP),
i.e. linear optimization problems over a
product of semidefinite cones, quadratic cones and the nonnegative orthant.
Together, these cones make up all possible homogeneous self-dual cones
over the reals.
The main routine implements a primal-dual Mehrotra predictor-corrector
scheme based on the XZ+ZX search direction.
The latest release of SDPpack is Version 0.9 beta.
This page contains links to the complete distribution,
binaries for some platforms, user guide, and a suite of
test problems. Download the version you
want from the tables below.
SDPpack Version 0.9 Beta for Matlab 5.0:
Semidefinite-Quadratic-Linearly constrained programs
Version 0.9 BETA
Solves SQLP's over the
non-negative orthant, the semidefinite cone and the quadratic
cone with a primal-dual interior-point predictor-corrector method using
the XZ+ZX search direction. Includes routines to solve special types of
semidefinite programs such as diagonally constrained and Lovasz theta
function problems, using the XZ method. Works within the Matlab
(Version 5.0) environment (optionally needs a C compiler to
build MEX files for improved performance).
Authors
Farid Alizadeh, Jean-Pierre A. Haeberly,
Madhu V. Nayakkankuppam, Michael L. Overton and Stefan Schmieta
Release date
June 26, 1997. See also the change log
file.
Distribution
Benchmarks
Sparc Ultra II
User Guide
HTML,
DVI and
PostScript
MEX binaries
Test problems
LMI, Truss, and Steiner tree problems
| Version 0.8 BETA | Solves semidefinite programs with a primal-dual interior-point predictor-corrector method using the XZ+ZX search direction. Includes routines to solve diagonally constrained and Lovasz theta function problems, using the XZ method. Works within the Matlab (Version 4.2c.1 or better) environment (optionally needs a C compiler to build MEX files for improved performance). |
| Authors | Farid Alizadeh, Jean-Pierre A. Haeberly, Madhu V. Nayakkankuppam and Michael L. Overton |
| Release date | March 28, 1997. See also the change log file. |
| Distribution | |
| Benchmarks | IRIX 6.2 (R10000) |
| User Guide | HTML, DVI and PostScript |
| MEX binaries | |
| Test problems | LMI and Truss problems |
Feedback and Bug Reports: The authors would like to hear your feedback and suggestions via email. The authors also welcome contributions of difficult test problems from application areas. If you are sending test problems, please formulate them as described in the SDPpack user manual and send us either mat files or ASCII files in the format described in the SDPpack user manual. A single data file may be emailed directly, but multiple files must be archived, compressed, encoded and emailed as a single file (avoid MIME encoding, please). If you are sending a bug report via email, please be sure to include the version, your platform and the exact data which causes the bug to show up. You can also use our Bug Report Submission Form.
Coming soon : A stand-alone, fast C version based on LAPACK, coming soon to a web site near you!
Copyright © 1997. All rights are reserved by the authors;
restrictions in the copyright notice in each release also apply.
SDPpack is software provided on an "as is" basis -- no
warranties, express or implied. In particular, the authors make no
representation about the merchantability of this software or its
fitness for any specific purpose. For research and noncommercial
use:
Last revised July 29, 1997.
This page has been made frame-free for your viewing pleasure.
Comments and suggestions to madhu@cs.nyu.edu