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Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems


  • David G. Dannenbring

    (University of North Carolina)


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

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    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. 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.
    3. 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.

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