Surrogate strategies for scalarisation-based multi-objective Bayesian optimizers

Mo, Q., Fialho Vilas Boas Duro, J.A. and Purshouse, R.C. (2025) Surrogate strategies for scalarisation-based multi-objective Bayesian optimizers. In: Singh, H., Ray, T., Knowles, J., Li, X., Branke, J., Wang, B. and Oyama, A., (eds.) Evolutionary Multi-Criterion Optimization (EMO 2025). 13th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2025), 04-07 Mar 2025, Canberra, Australia. Lecture Notes in Computer Science, 15513 . Springer Cham ISBN 978-981-96-3538-2

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • Mo, Q.
  • Fialho Vilas Boas Duro, J.A.
  • Purshouse, R.C.
Editors:
  • Singh, H.
  • Ray, T.
  • Knowles, J.
  • Li, X.
  • Branke, J.
  • Wang, B.
  • Oyama, A.
Copyright, Publisher and Additional Information:

© 2025 The Author(s). Except as otherwise noted, this author-accepted version of a proceedings paper published in Evolutionary Multi-Criterion Optimization (EMO 2025) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Bayesian Optimization; Multi-objective Optimization; Benchmark Problems; Surrogate Modelling
Dates:
  • Published: 28 February 2025
  • Published (online): 28 February 2025
  • Accepted: 16 November 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:
Funder
Grant number
MEDICAL RESEARCH COUNCIL
MR/S037578/1
Depositing User: Symplectic Sheffield
Date Deposited: 15 Jan 2025 10:12
Last Modified: 03 Mar 2025 15:26
Status: Published
Publisher: Springer Cham
Series Name: Lecture Notes in Computer Science
Refereed: Yes
Related URLs:
Open Archives Initiative ID (OAI ID):

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