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Reactive Flexible Job Shop Problem with Stress Level Consideration

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Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures (APMS 2023)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 691))

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Abstract

Taking into account a real-world issue, the present study focuses on a flexible job shop scheduling problem (FJSSP) that deals with new job arrivals. This problem is very common in real-world manufacturing operations. On the other hand, Industry 5.0 environment pays more attention to human resources, and it is shown that well-being of workers including the stress level of them has a great impact on shop scheduling performance performance. However, with the arrival of a new job, the initial planning needs a rescheduling and these changes on the initial schedule may increase the stress level of workers. Still, given the real-world problem, we want to minimize the stress level of different rescheduling strategies. Three types of changes will be imposed to the shop floor schedule, which could lead to an increased stress level on human resources. These changes are as follows: 1 - Shifting an old operation on the same machine when the new job arrives; 2 - changing the machine assigned to an operation; 3 - altering the sequence of the operations.

The procedure for calculating the different kinds of changes affected by the new job arrivals is illustrated in order to find the level of imposed stress. To solve such an NP-Hard problem, a Genetic Algorithm (GA) is investigated to solve it. At first an initial schedule is built based on benchmark instances from FJSSP literature. Then, at different times, new jobs will arrive, with routes taken from the same instance. The instances are used to validate the proposed algorithm. Behavior of the algorithm on very large problems indicates that obtained schedules remain as compact as expected while considering the stress criterion.

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Acknowledgement

The authors gratefully acknowledge the financial support of the Region Auvergne-Rhône-Alpes under project “PSPC Régions AAP 2 - Easy Smart Factory”, and the members of the project’s consortium.

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Authors and Affiliations

  1. Mines Saint-Etienne, Univ Clermont Auvergne, INP Clermont Auvergne, CNRS, UMR 6158 LIMOS, 42023, Saint-Etienne, France

    Ehsan Yadegari, Damien Lamy & Xavier Delorme

Authors
  1. Ehsan Yadegari
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  2. Damien Lamy
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  3. Xavier Delorme
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Corresponding author

Correspondence to Ehsan Yadegari .

Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Erlend Alfnes

  2. Norwegian University of Science and Technology, Trondheim, Norway

    Anita Romsdal

  3. Norwegian University of Science and Technology, Trondheim, Norway

    Jan Ola Strandhagen

  4. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Gregor von Cieminski

  5. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

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Yadegari, E., Lamy, D., Delorme, X. (2023). Reactive Flexible Job Shop Problem with Stress Level Consideration. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 691. Springer, Cham. https://doi.org/10.1007/978-3-031-43670-3_44

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  • DOI: https://doi.org/10.1007/978-3-031-43670-3_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43669-7

  • Online ISBN: 978-3-031-43670-3

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