MVMOO: Mixed variable multi-objective optimisation

Manson, JA orcid.org/0000-0001-7392-3197, Chamberlain, TW orcid.org/0000-0001-8100-6452 and Bourne, RA orcid.org/0000-0001-7107-6297 (2021) MVMOO: Mixed variable multi-objective optimisation. Journal of Global Optimization, 80. pp. 865-886. ISSN 0925-5001

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Global optimisation; Hypervolume; Multi-objective; Mixed variable; Bayesian optimisation
Dates:
  • Published: August 2021
  • Accepted: 25 May 2021
  • Published (online): 9 July 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds)
The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemistry (Leeds) > Inorganic Chemistry (Leeds)
Funding Information:
FunderGrant number
EPSRC (Engineering and Physical Sciences Research Council)EP/R032807/1
Royal Academy of EngineeringRCSRF1920\9\38
Depositing User: Symplectic Publications
Date Deposited: 03 Jun 2021 15:17
Last Modified: 30 Nov 2021 16:10
Status: Published
Publisher: Springer
Identification Number: https://doi.org/10.1007/s10898-021-01052-9

Share / Export

Statistics