IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v23y1977i12p1273-1283.html
   My bibliography  Save this article

Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems

Author

Listed:
  • David G. Dannenbring

    (University of North Carolina)

Abstract

This study focuses attention on methods for generating useful solution standards for large combinatorial problems. In particular, several procedures that provide point estimates of the value of the optimum solution are suggested and tested. These concepts are applied to a representative combinatorial problem: flow shop sequencing. Detailed computational results are presented.

Suggested Citation

  • David G. Dannenbring, 1977. "Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems," Management Science, INFORMS, vol. 23(12), pages 1273-1283, August.
  • Handle: RePEc:inm:ormnsc:v:23:y:1977:i:12:p:1273-1283
    DOI: 10.1287/mnsc.23.12.1273
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.23.12.1273
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.23.12.1273?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. Kenneth Carling & Xiangli Meng, 2015. "Confidence in heuristic solutions?," Journal of Global Optimization, Springer, vol. 63(2), pages 381-399, October.
    2. Rinnooy Kan, A. H. G., 1985. "Probabilistic Analysis Of Algorithms," Econometric Institute Archives 272328, Erasmus University Rotterdam.
    3. Robert L. Nydick & Howard J. Weiss, 1994. "An analytical evaluation of optimal solution value estimation procedures," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(2), pages 189-202, March.
    4. Wilson, Amy D. & King, Russell E. & Wilson, James R., 2004. "Case study on statistically estimating minimum makespan for flow line scheduling problems," European Journal of Operational Research, Elsevier, vol. 155(2), pages 439-454, June.
    5. Kenneth Carling & Xiangli Meng, 2016. "On statistical bounds of heuristic solutions to location problems," Journal of Combinatorial Optimization, Springer, vol. 31(4), pages 1518-1549, May.
    6. Bettinger, Pete & Boston, Kevin & Kim, Young-Hwan & Zhu, Jianping, 2007. "Landscape-level optimization using tabu search and stand density-related forest management prescriptions," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1265-1282, January.

    More about this item

    Statistics

    Access and download statistics

    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:ormnsc:v:23:y:1977:i:12:p:1273-1283. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.