Interior-Point Methods Online

Interior-Point Methods Online

Dear Colleagues,

The Interior-Point Methods Online
site is no longer maintained.

If you are looking for recent reports on
interior-point methods (from 2001 onwards), or if you wish to post
your new report on an online archive, please go to
Optimization Online.
Reports on interior-point methods can be found on this site
in the sections on Linear, Cone and Semidefinite Programming,
Nonlinear Optimization, and other categories. You can also search the Optimization Online
site by author name or keyword.

This archive of interior-point reports will be left online indefinitely.
You are urged to contact the authors to obtain the latest versions of
any reports that catch your interest, or to obtain a reference to the
published version.

Best regards,

Steve Wright
( )

From here, you can

Other fun things to do:

Click here for the Archive of Papers

Interior-Point People and Places

Here are some pointers to

  • home pages of interior-point researchers
  • places where interior-point work is done.

To suggest additions to this list (including your own pages) go to our suggestions box.



  • OOPS, an object-oriented parallel implementation of the interior point
    algorithm developed by Jacek Gondzio,
    Andreas Grothey and Robert Sarkissian. The code can exploit special structure
    of the application. It runs on all parallel computing platforms that
    support MPI.

  • MOSEK, an implementation of the
    homogeneous interior-point algorithm for linear and convex optimization.

  • The CPLEX Barrier Solver
    page-CPLEX’s interior-point option.
  • Dash Associates, whose products include the
    “Primal Barrier XPRESS-MP,” a primal-dual interior-point code.
  • The CPnet page (CP = complementarity
    problems). The interior-point approach is one of three or four approaches being used to
    solve complementarity problems.
  • The Math Programming page at the
    University of Wisconsin-Madison.
  • Semidefinite programming pages are maintained by
  • Christoph Helmberg,
  • Mike Todd,
  • Henry Wolkowicz.
  • OSL-IBM’s Optimization Subroutine
    Library-contains a primal-dual code with a number of algorithmic options.
  • The Optimization Technology Center at Argonne and
    Northwestern, and the NEOS Server,
    which includes the linear programming code PCx among its roster of solvers. You can submit
    an MPS file to NEOS through the Internet, using email, the WWW, or-the sexiest option-a
    customized submission tool. NEOS solves the problem and returns the results.
  • PCx, the NEOS project’s
    primal-dual code.
  • Home page for the book Primal-Dual
    Interior-Point Methods
    by Steve Wright. Contains links to further information on
    primal-dual codes.
  • Mathematical
    Programming Glossary
    maintained by Harvey Greenberg.
  • A group of IE students at Berkeley have built a nice interactive demo of linear
    programming. It allows you to enter a 2D problem, solve it, and view the results
  • Silicon
    has an operations research page, which includes information about a parallel
    implementation of CPLEX/Barrier.
  • Home page for a new book called Advances
    in Linear and Integer Programming
    (J. E. Beasley, ed., Oxford University Press).
    This is another collection of papers that includes four or five papers on interior-point
  • Home page for the book called Theory and
    Algorithms for Linear Optimization: An Interior Point Approach
    by C. Roos, T.
    Terlaky, and J.-P. Vial, recently published by John Wiley and Sons.
  • Home page for the book called Interior
    Point Methods of Mathematical Programming
    (T. Terlaky, editor), recently published
    by Kluwer.

  • Conference Announcements, Comments, and News


    This area is maintained by Nathan Brixius
    and Steve Wright at Argonne National

    Two undergraduate students at Argonne-Rich Marynowski and Tim Wisniewski-did a lot to
    build and maintain this archive during their respective visits. Marianne Stone chipped in
    with some tasteful graphics. Thanks!

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