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

Dziurzanski, Piotr, Zhao, Shuai, Swan, Jerry et al. (3 more authors) (2019) Solving the Multi-Objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process. In: Kaufmann, Paul and Castillo, Pedro A., (eds.) Applications of Evolutionary Computation - 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer, pp. 33-48.

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Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Kaufmann, Paul
  • Castillo, Pedro A.
Copyright, Publisher and Additional Information:

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.
Keywords: Multi-objective genetic algorithms,Multi-objective job-shop scheduling,Process manufacturing optimisation
Dates:
  • Accepted: 5 January 2019
  • Published (online): 30 March 2019
  • Published: 24 April 2019
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 01 May 2019 08:50
Last Modified: 17 Sep 2025 04:37
Published Version: https://doi.org/10.1007/978-3-030-16692-2_3
Status: Published
Publisher: Springer
Series Name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Identification Number: 10.1007/978-3-030-16692-2_3
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Open Archives Initiative ID (OAI ID):

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