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Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

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Book cover Applications of Evolutionary Computation (EvoApplications 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11454))

Abstract

This paper considers a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes. We propose a novel associated chromosome encoding and customise the classic MOEA/D multi-objective genetic algorithm with new genetic operators. The applicability of the proposed approach is evaluated experimentally and showed to outperform typical multi-objective genetic algorithms. The problem variant is motivated by real-world manufacturing in a chemical plant and is applicable to other plants that manufacture goods using alternative recipes.

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Notes

  1. 1.

    Note, due to the applied value encoding, a recipe instance can either be allocated to a resource among its feasible allocations or not be allocated at all. A recipe that is not allocated will be not scheduled for manufacturing.

  2. 2.

    In general, each numerical value in a tuple obtained with DCI corresponds to a certain front quality in relation to the remaining fronts under comparison. These values are upperbonded with 1 and a higher value denotes a better relative front quality.

  3. 3.

    For two solutions p and q, p strictly dominates q if p has a better value than q for any objective.

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Acknowledgement

The authors acknowledge the support of the EU H2020 SAFIRE project (Ref. 723634).

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Authors and Affiliations

  1. Department of Computer Science, University of York, Deramore Lane, Heslington, York, YO10 5GH, UK

    Piotr Dziurzanski, Shuai Zhao, Jerry Swan & Leandro Soares Indrusiak

  2. Institut fur Angewandte Systemtechnik Bremen GmbH, Wiener Strasse 1, 28359, Bremen, Germany

    Sebastian Scholze

  3. OAS AG, Caroline-Herschel-Strasse 1, 28359, Bremen, Germany

    Karl Krone

Authors
  1. Piotr Dziurzanski
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  2. Shuai Zhao
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  3. Jerry Swan
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  4. Leandro Soares Indrusiak
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  5. Sebastian Scholze
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  6. Karl Krone
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Corresponding author

Correspondence to Piotr Dziurzanski .

Editor information

Editors and Affiliations

  1. University of Mainz, Mainz, Germany

    Paul Kaufmann

  2. University of Granada, Granada, Spain

    Pedro A. Castillo

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Dziurzanski, P., Zhao, S., Swan, J., Indrusiak, L.S., Scholze, S., Krone, K. (2019). Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process. In: Kaufmann, P., Castillo, P. (eds) Applications of Evolutionary Computation. EvoApplications 2019. Lecture Notes in Computer Science(), vol 11454. Springer, Cham. https://doi.org/10.1007/978-3-030-16692-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-16692-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16691-5

  • Online ISBN: 978-3-030-16692-2

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