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An improved branch and bound algorithm for a strongly correlated unbounded knapsack problem

Author

Listed:
  • Y-J Seong

    (Hanyang University)

  • Y-G G

    (Hanyang University)

  • M-K Kang

    (Hanyang University)

  • C-W Kang

    (Hanyang University)

Abstract

An unbounded knapsack problem (KP) was investigated that describes the loading of items into a knapsack with a finite capacity, W, so as to maximize the total value of the loaded items. There were n types of an infinite number of items, each type with a distinct weight and value. Exact branch and bound algorithms have been successfully applied previously to the unbounded KP, even when n and W were very large; however, the algorithms are not adequate when the weight and the value of the items are strongly correlated. An improved branching strategy is proposed that is less sensitive to such a correlation; it can therefore be used for both strongly correlated and uncorrelated problems.

Suggested Citation

  • Y-J Seong & Y-G G & M-K Kang & C-W Kang, 2004. "An improved branch and bound algorithm for a strongly correlated unbounded knapsack problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 547-552, May.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:5:d:10.1057_palgrave.jors.2601698
    DOI: 10.1057/palgrave.jors.2601698
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    References listed on IDEAS

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