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Binary knapsack problems with random budgets

Author

Listed:
  • S Das

    (QM&IS Area, Indian Institute of Management)

  • D Ghosh

    (P&QM Area, Indian Institute of Management)

Abstract

The binary knapsack problem is a combinatorial optimization problem in which a subset of a given set of elements needs to be chosen in order to maximize profit, given a budget constraint. In this paper, we study a stochastic version of the problem in which the budget is random. We propose two different formulations of this problem, based on different ways of handling infeasibility, and propose an exact algorithm and a local search-based heuristic to solve the problems represented by these formulations. We also present the results from some computational experiments.

Suggested Citation

  • S Das & D Ghosh, 2003. "Binary knapsack problems with random budgets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(9), pages 970-983, September.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:9:d:10.1057_palgrave.jors.2601596
    DOI: 10.1057/palgrave.jors.2601596
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    References listed on IDEAS

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    1. Gang Yu, 1996. "On the Max-Min 0-1 Knapsack Problem with Robust Optimization Applications," Operations Research, INFORMS, vol. 44(2), pages 407-415, April.
    2. Ghosh, D. & Das, S., 2000. "Discrete optimization problems with random cost elements," Research Report 00A33, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    3. Egon Balas, 1965. "An Additive Algorithm for Solving Linear Programs with Zero-One Variables," Operations Research, INFORMS, vol. 13(4), pages 517-546, August.
    4. Mordechai I. Henig, 1990. "Risk Criteria in a Stochastic Knapsack Problem," Operations Research, INFORMS, vol. 38(5), pages 820-825, October.
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    Cited by:

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    2. João Claro & Jorge Sousa, 2010. "A multiobjective metaheuristic for a mean-risk static stochastic knapsack problem," Computational Optimization and Applications, Springer, vol. 46(3), pages 427-450, July.

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