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

  • Technical Note
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Journal of the Operational Research Society

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.

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Authors and Affiliations

  1. Hanyang University, South Korea

    Y-J Seong, Y-G G, M-K Kang & C-W Kang

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  1. Y-J Seong
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  2. Y-G G
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  3. M-K Kang
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  4. C-W Kang
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Correspondence to Y-J Seong.

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Seong, YJ., G, YG., Kang, MK. et al. An improved branch and bound algorithm for a strongly correlated unbounded knapsack problem. J Oper Res Soc 55, 547–552 (2004). https://doi.org/10.1057/palgrave.jors.2601698

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  • DOI: https://doi.org/10.1057/palgrave.jors.2601698

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