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

Seong Y-J (), Y-G G, Kang M-K and Kang C-W
Additional contact information
Seong Y-J: Hanyang University
Y-G G: Hanyang University
Kang M-K: Hanyang University
Kang C-W: Hanyang University

Journal of the Operational Research Society, 2004, vol. 55, issue 5, 547-552

Abstract: 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.

Keywords: knapsack problem; branch and bound; combinatorial optimization; exact algorithm (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1057/palgrave.jors.2601698

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