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Data aggregation for p-median problems

Author

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  • Bader F. AlBdaiwi

    (Kuwait University)

  • Diptesh Ghosh

    (Indian Institute of Management)

  • Boris Goldengorin

    (University of Groningen)

Abstract

In this paper, we use a pseudo-Boolean formulation of the p-median problem and using data aggregation, provide a compact representation of p-median problem instances. We provide computational results to demonstrate this compactification in benchmark instances. We then use our representation to explain why some p-median problem instances are more difficult to solve to optimality than other instances of the same size. We also derive a preprocessing rule based on our formulation, and describe equivalent p-median problem instances, which are identical sized instances which are guaranteed to have identical optimal solutions.

Suggested Citation

  • Bader F. AlBdaiwi & Diptesh Ghosh & Boris Goldengorin, 2011. "Data aggregation for p-median problems," Journal of Combinatorial Optimization, Springer, vol. 21(3), pages 348-363, April.
    • Handle: RePEc:spr:jcomop:v:21:y:2011:i:3:d:10.1007_s10878-009-9251-8
    DOI: 10.1007/s10878-009-9251-8
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    References listed on IDEAS

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    Cited by:

    1. Buchheim, Christoph & Crama, Yves & Rodríguez-Heck, Elisabeth, 2019. "Berge-acyclic multilinear 0–1 optimization problems," European Journal of Operational Research, Elsevier, vol. 273(1), pages 102-107.
    2. Boris Goldengorin & Dmitry Krushinsky & Jannes Slomp, 2012. "Flexible PMP Approach for Large-Size Cell Formation," Operations Research, INFORMS, vol. 60(5), pages 1157-1166, October.

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