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A heuristic routine for solving large loading problems

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  • John C. Fisk
  • Ming S. Hung

Abstract

The loading problem involves the optimal allocation of n objects, each having a specified weight and value, to m boxes, each of specified capacity. While special cases of these problems can be solved with relative ease, the general problem having variable item weights and box sizes can become very difficult to solve. This paper presents a heuristic procedure for solving large loading problems of the more general type. The procedure uses a surrogate procedure for reducing the original problem to a simpler knapsack problem, the solution of which is then employed in searching for feasible solutions to the original problem. The procedure is easy to apply, and is capable of identifying optimal solutions if they are found.

Suggested Citation

  • John C. Fisk & Ming S. Hung, 1979. "A heuristic routine for solving large loading problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 26(4), pages 643-650, December.
  • Handle: RePEc:wly:navlog:v:26:y:1979:i:4:p:643-650
    DOI: 10.1002/nav.3800260409
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    Cited by:

    1. Dell’Amico, Mauro & Delorme, Maxence & Iori, Manuel & Martello, Silvano, 2019. "Mathematical models and decomposition methods for the multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 274(3), pages 886-899.
    2. Olivier Lalonde & Jean-François Côté & Bernard Gendron, 2022. "A Branch-and-Price Algorithm for the Multiple Knapsack Problem," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3134-3150, November.

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