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Robust Scheduling with Logic-Based Benders Decomposition

In: Operations Research Proceedings 2014

Author

Listed:
  • Elvin Coban

    (Özyeǧin University)

  • Aliza Heching

    (IBM Thomas J. Watson Research Center)

  • J. N. Hooker

    (Carnegie Mellon University)

  • Alan Scheller-Wolf

    (Carnegie Mellon University)

Abstract

We study project scheduling at a large IT services delivery center in which there are unpredictable delays. We apply robust optimization to minimize tardiness while informing the customer of a reasonable worst-case completion time, based on empirically determined uncertainty sets. We introduce a new solution method based on logic-based Benders decomposition. We show that when the uncertainty set is polyhedral, the decomposition simplifies substantially, leading to a model of tractable size. Preliminary computational experience indicates that this approach is superior to a mixed integer programming model solved by state-of-the-art software.

Suggested Citation

  • Elvin Coban & Aliza Heching & J. N. Hooker & Alan Scheller-Wolf, 2016. "Robust Scheduling with Logic-Based Benders Decomposition," Operations Research Proceedings, in: Marco Lübbecke & Arie Koster & Peter Letmathe & Reinhard Madlener & Britta Peis & Grit Walther (ed.), Operations Research Proceedings 2014, edition 1, pages 99-105, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-28697-6_15
    DOI: 10.1007/978-3-319-28697-6_15
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    Cited by:

    1. Silva, Marco & Poss, Michael & Maculan, Nelson, 2020. "Solution algorithms for minimizing the total tardiness with budgeted processing time uncertainty," European Journal of Operational Research, Elsevier, vol. 283(1), pages 70-82.

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