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Solving a real-life multi-skill resource-constrained multi-project scheduling problem

Author

Listed:
  • Rahman Torba

    (Mines Saint-Etienne, Univ Clermont Auvergne CNRS, UMR, LIMOS
    SNCF)

  • Stéphane Dauzère-Pérès

    (Mines Saint-Etienne, Univ Clermont Auvergne CNRS, UMR, LIMOS
    BI Norwegian Business School)

  • Claude Yugma

    (Mines Saint-Etienne, Univ Clermont Auvergne CNRS, UMR, LIMOS)

  • Cédric Gallais

    (SNCF)

  • Juliette Pouzet

    (SNCF)

Abstract

This paper addresses a multi-skill resource-constrained multi-project scheduling problem (MSRCMPSP) with different types of resources and complex industrial constraints, which originates from SNCF heavy maintenance factories. Two objective functions, that have been rarely addressed in the literature, are independently considered: (i) Minimization of the sum of the weighted tardiness of the projects and (ii) Minimization of the sum of the weighted duration of the projects. A time-indexed mixed-integer linear programming model is presented with both resource assignment and capacity constraints. To solve large instances with several thousand activities, a new memetic algorithm combining a novel hybrid simulated genetic algorithm with a simulated annealing is implemented. The memetic algorithm is compared with popular solution approaches. Computational experiments conducted on real instances and benchmark instances validate the efficiency of the proposed algorithm.

Suggested Citation

  • Rahman Torba & Stéphane Dauzère-Pérès & Claude Yugma & Cédric Gallais & Juliette Pouzet, 2024. "Solving a real-life multi-skill resource-constrained multi-project scheduling problem," Annals of Operations Research, Springer, vol. 338(1), pages 69-114, July.
    • Handle: RePEc:spr:annopr:v:338:y:2024:i:1:d:10.1007_s10479-023-05784-7
    DOI: 10.1007/s10479-023-05784-7
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