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Computational results with a branch‐and‐bound algorithm for the general knapsack problem

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  • R. L. Bulfin
  • R. G. Parker
  • C. M. Shetty

Abstract

In this paper, a branch‐and‐bound procedure is presented for treating the general knapsack problem. The fundamental notion of the procedure involves a variation of traditional branching strategies as well as the incorporation of penalties in order to improve bounds. Substantial computational experience has been obtained, the results of which would indicate the feasibility of the procedure for problems of large size.

Suggested Citation

  • R. L. Bulfin & R. G. Parker & C. M. Shetty, 1979. "Computational results with a branch‐and‐bound algorithm for the general knapsack problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 26(1), pages 41-46, March.
    • Handle: RePEc:wly:navlog:v:26:y:1979:i:1:p:41-46
    DOI: 10.1002/nav.3800260105
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    Cited by:

    1. Chia‐Shin Chung & Ming S. Hung & Walter O. Rom, 1988. "A hard knapsack problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(1), pages 85-98, February.
    2. Shin, Dong Wan & Park, Chul Gyu & Park, Taesung, 2001. "Testing for one-sided group effects in repeated measures study," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 233-247, August.
    3. Barniv, Ran & Mehrez, Abraham & Kline, Douglas M., 2000. "Confidence intervals for controlling the probability of bankruptcy," Omega, Elsevier, vol. 28(5), pages 555-565, October.
    4. D'Urso, Pierpaolo, 2003. "Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 47-72, February.

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