SDPpack: A package for semidefinite-quadratic-linear programming (SQLP)


Table of Contents


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
  • Complete UNIX distribution (sdppack.tar.gz) (does not contain MEX files)
  • Complete Windows NT / 95 distribution (sdppack.zip) (includes compiled .dll files)
  • Complete MacOS (PowerPC) distribution (sdppack.sea.hqx) (self-extracting archive includes compiled .mex files)
  • Benchmarks Sparc Ultra II
    User Guide HTML, DVI and PostScript
    MEX binaries
  • AIX (RS6000)
  • IRIX 6.2 (R10000/8000)
  • IRIX 6.3 (R5000)
  • IRIX 5.3 (R4400/4000)
  • SunOS 4.1.4 (Sparc)
  • SunOS 5.5.1 (Sparc)
  • Windows NT / 95 (x86)
  • Test problems LMI, Truss, and Steiner tree problems


    SDPpack Version 0.8 Beta for Matlab 4.2:
    Semidefinite Programs

    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
  • Complete UNIX distribution (sdppack.tar.gz) (does not contain MEX files)
  • Complete Windows NT / 95 distribution (sdppack.zip) (contains compiled .dll files)
  • Benchmarks IRIX 6.2 (R10000)
    User Guide HTML, DVI and PostScript
    MEX binaries
  • IRIX 6.2 (R10000/R8000)
  • IRIX 5.3 (R4000/R4400)
  • AIX (RS6000)
  • SunOS 4.1.4 (Sparc)
  • Sun OS 5.5.1 (Sparc)
  • Windows NT / 95 (x86)
  • 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