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Local Search for Integrated Predictive Maintenance and Scheduling in Flow-Shop

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Metaheuristics (MIC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13838))

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Abstract

We address the Permutation Flow-Shop Scheduling Problem with Predictive Maintenance presented by Varnier and Zerhouni (2012), that consists in finding the integrated schedule for production and maintenance tasks such that the total production time and the advance of maintenance services are minimized. Predictive maintenance services are scheduled based on a prognostics system that is able to provide the remaining useful life of a machine. To solve this problem, we propose a local search method with neighborhoods specifically tailored for maintenance interventions. Computational experiments performed on generated benchmarks demonstrate the effectiveness and scalability of our method with respect to an exact technique based on the mathematical model proposed by Varnier and Zerhouni (2012).

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Acknowledgement

We thank Hildarahi Luz Orihuela Lino for developing the preliminary version of the mathematical model.

This work has been co-funded by the ERDF-ROP (2014–2020), Friuli Venezia Giulia (Italy), Axis 1, Action 1.3.

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Authors and Affiliations

  1. DPIA, University of Udine, via delle Scienze 206, 33100, Udine, Italy

    Andrea Ecoretti, Sara Ceschia & Andrea Schaerf

Authors
  1. Andrea Ecoretti
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  2. Sara Ceschia
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  3. Andrea Schaerf
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Corresponding author

Correspondence to Andrea Schaerf .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Luca Di Gaspero

  2. University of Napoli - Federico II, Napoli, Italy

    Paola Festa

  3. University of Paris Est, Paris, France

    Amir Nakib

  4. University of Catania, Catania, Italy

    Mario Pavone

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Ecoretti, A., Ceschia, S., Schaerf, A. (2023). Local Search for Integrated Predictive Maintenance and Scheduling in Flow-Shop. In: Di Gaspero, L., Festa, P., Nakib, A., Pavone, M. (eds) Metaheuristics. MIC 2022. Lecture Notes in Computer Science, vol 13838. Springer, Cham. https://doi.org/10.1007/978-3-031-26504-4_19

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  • DOI: https://doi.org/10.1007/978-3-031-26504-4_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-26503-7

  • Online ISBN: 978-3-031-26504-4

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