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Multi-objective Particle Swarm Optimisation for Robust Dynamic Scheduling in a Permutation Flow Shop

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

This paper proposes a multi-objective optimisation model and particle swarm optimisation solution method for the robust dynamic scheduling of permutation flow shop in the presence of uncertainties. The proposed optimisation model for robust scheduling considers utility, stability and robustness measures to generate robust schedules that minimise the effect of different real-time events on the planned schedule. The proposed solution method is based on a predictive-reactive approach that uses particle swarm optimisation to generate robust schedules in the presence of real-time events. The evaluation of both the optimisation model and solution method are conducted considering different types of disruptions including machine breakdown and new job arrival. The obtained results showed that the proposed model and solution method gives better results than a bi-objective model that considers only utility and stability measures [1] and the classical makespan model.

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Author information

Authors and Affiliations

  1. University of Basra, Basra, Iraq

    Mohanad Al-Behadili

  2. Department of Mathematics, University of Portsmouth, Lion Gate Building, Portsmouth, PO1 3HF, UK

    Mohanad Al-Behadili, Djamila Ouelhadj & Dylan Jones

Authors
  1. Mohanad Al-Behadili
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  2. Djamila Ouelhadj
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  3. Dylan Jones
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Corresponding author

Correspondence to Mohanad Al-Behadili .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Al-Behadili, M., Ouelhadj, D., Jones, D. (2017). Multi-objective Particle Swarm Optimisation for Robust Dynamic Scheduling in a Permutation Flow Shop. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_49

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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