A scalable test suite for bi-objective multidisciplinary optimization

Johnson, V., Duro, J.A. orcid.org/0000-0002-7684-4707, Kadirkamanathan, V. et al. (1 more author) (2023) A scalable test suite for bi-objective multidisciplinary optimization. In: Emmerich, M., Deutz, A., Wang, H., Kononova, A.V., Naujoks, B., Li, K., Miettinen, K. and Yevseyeva, I., (eds.) Evolutionary Multi-Criterion Optimization: 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings. 12th International Conference, Evolutionary Multi-Criterion Optimization (EMO2023), 20-24 Mar 2023, Leiden, Netherlands. Lecture Notes in Computer Science (LNCS 13970). Springer , pp. 319-332. ISBN 9783031272493

Abstract

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Item Type: Proceedings Paper
Authors/Creators:
Copyright, Publisher and Additional Information: © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is an author-produced version of a paper subsequently published in Evolutionary Multi-Criterion Optimization: 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings, Lecture Notes in Computer Science, vol 13970. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: multidisciplinary design optimization; multi-objective optimization; benchmark problems; scalability
Dates:
  • Accepted: 7 December 2022
  • Published (online): 9 March 2023
  • Published: 9 March 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 19 Jan 2023 17:26
Last Modified: 09 Mar 2024 01:13
Status: Published
Publisher: Springer
Series Name: Lecture Notes in Computer Science
Refereed: Yes
Identification Number: https://doi.org/10.1007/978-3-031-27250-9_23
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