IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v4y1992i2p166-181.html
   My bibliography  Save this article

Massively Parallel Algorithms for Singly Constrained Convex Programs

Author

Listed:
  • Soren S. Nielsen

    (Decision Sciences Department, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104)

  • Stavros A. Zenios

    (Decision Sciences Department, The Wharton School, University of Pennsylvania, Philadelphia, PA 19194)

Abstract

We develop four iterative algorithms for the solution of separable, convex nonlinear optimization problems with a single linear constraint and bounded variables. The design of the algorithms makes them suitable for implementation on massively parallel computers of the SIMD (i.e., Single Instruction, Multiple Data) class. The algorithms are specialized for the solution of network problems whereby the linear constraint reflects conservation of flow. Details of implementations on a Connection Machine CM-2 are reported. The numerical results indicate that all algorithms are very effective, and can solve very large problems. Three of the algorithms are also very efficient when implemented on the massively parallel system. Interestingly, the most effective algorithm (in number of steps required to solve the test problems) is the least efficient (in solution time) when implemented in parallel. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

Suggested Citation

  • Soren S. Nielsen & Stavros A. Zenios, 1992. "Massively Parallel Algorithms for Singly Constrained Convex Programs," INFORMS Journal on Computing, INFORMS, vol. 4(2), pages 166-181, May.
  • Handle: RePEc:inm:orijoc:v:4:y:1992:i:2:p:166-181
    DOI: 10.1287/ijoc.4.2.166
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.4.2.166
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. K. C. Kiwiel, 2008. "Variable Fixing Algorithms for the Continuous Quadratic Knapsack Problem," Journal of Optimization Theory and Applications, Springer, vol. 136(3), pages 445-458, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orijoc:v:4:y:1992:i:2:p:166-181. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matthew Walls). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.