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

Dziurzanski, Piotr orcid.org/0000-0001-9542-652X, 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) . , pp. 33-48.

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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,Theoretical Computer Science,Computer Science
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: 24 Apr 2021 23:58
Published Version: https://doi.org/10.1007/978-3-030-16692-2_3
Status: Published
Series Name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Refereed: No
Identification Number: https://doi.org/10.1007/978-3-030-16692-2_3
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