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A Cardinality-constrained Approach for Robust Machine Loading Problems

Author

Listed:
  • Giovanni Lugaresi

    (LGI - Laboratoire Génie Industriel - CentraleSupélec - Université Paris-Saclay)

  • Ettore Lanzarone

    (Istituto di Analisi dei Sistemi e Informatica - CNR - Istituto di Analisi dei Sistemi e Informatica - CNR)

  • Nicola Frigerio
  • Andrea Matta

    (POLIMI - Politecnico di Milano [Milan])

Abstract

The Machine Loading Problem (MLP) refers to the allocation of operative tasks and tools to machines for the production of parts. Since the uncertainty of processing times might affect the quality of the solution, this paper proposes a robust formulation of an MLP, based on the cardinality-constrained approach, to evaluate the optimal solution in the presence of a given number of fluctuations of the actual processing time with respect to the nominal one. The applicability of the model in the practice has been tested on a case study.

Suggested Citation

  • Giovanni Lugaresi & Ettore Lanzarone & Nicola Frigerio & Andrea Matta, 2017. "A Cardinality-constrained Approach for Robust Machine Loading Problems," Post-Print hal-03880625, HAL.
    • Handle: RePEc:hal:journl:hal-03880625
    DOI: 10.1016/j.promfg.2017.07.298
    Note: View the original document on HAL open archive server: https://hal.science/hal-03880625
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    References listed on IDEAS

    as
    1. Kathryn E. Stecke, 1983. "Formulation and Solution of Nonlinear Integer Production Planning Problems for Flexible Manufacturing Systems," Management Science, INFORMS, vol. 29(3), pages 273-288, March.
    2. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    3. F. Guerrero & S. Lozano & T. Koltai & J. Larrañeta, 1999. "Machine loading and part type selection in flexible manufacturing systems," International Journal of Production Research, Taylor & Francis Journals, vol. 37(6), pages 1303-1317, April.
    4. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
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