Multiobjective optimization by using cutting angle methods and hypervolume criterion

Beliakov, G; Gao, L; Xiang, Y; Zhou, W

Multiobjective optimization by using cutting angle methods and hypervolume criterion

Beliakov, G Gao, L Xiang, Y Zhou, W

Permalink

Publisher:: Taylor and Francis Group
Publication Type:: Journal Article
Citation:: Optimization Methods and Software, 2025, 40, (2), pp. 388-405
Issue Date:: 2025-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (2.15 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Beliakov, G
dc.contributor.author	Gao, L
dc.contributor.author	Xiang, Y
dc.contributor.author	Zhou, W https://orcid.org/0000-0002-1680-2521
dc.date.accessioned	2025-08-06T03:45:57Z
dc.date.available	2025-08-06T03:45:57Z
dc.date.issued	2025-01-01
dc.identifier.citation	Optimization Methods and Software, 2025, 40, (2), pp. 388-405
dc.identifier.issn	1055-6788
dc.identifier.issn	1029-4937
dc.identifier.uri	http://hdl.handle.net/10453/189101
dc.description.abstract	We translate a multiobjective optimization problem into a single objective Lipschitz problem by using the hypervolume criterion of the Pareto set. Deterministic global optimization methods allow one to track the whole Pareto front rather than converging to a single non-dominated solution. We augmented an efficient hypervolume computation technique with hypervolume increment strategy, and established Lipschitzianity of the resulting objective function. We used two deterministic Lipschitz optimization methods together with the hypervolume objective and benchmarked them against some state-of-the-art alternative multiobjective optimization methods, establishing the competitiveness of the proposed approach.
dc.language	en
dc.publisher	Taylor and Francis Group
dc.relation	http://purl.org/au-research/grants/arc/LP170100458
dc.relation.ispartof	Optimization Methods and Software
dc.relation.isbasedon	10.1080/10556788.2024.2405984
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0102 Applied Mathematics, 0103 Numerical and Computational Mathematics, 0802 Computation Theory and Mathematics
dc.subject.classification	Operations Research
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4901 Applied mathematics
dc.subject.classification	4903 Numerical and computational mathematics
dc.title	Multiobjective optimization by using cutting angle methods and hypervolume criterion
dc.type	Journal Article
utslib.citation.volume	40
utslib.for	0102 Applied Mathematics
utslib.for	0103 Numerical and Computational Mathematics
utslib.for	0802 Computation Theory and Mathematics
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2025-08-06T03:45:55Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	40
utslib.citation.issue	2

Abstract:

We translate a multiobjective optimization problem into a single objective Lipschitz problem by using the hypervolume criterion of the Pareto set. Deterministic global optimization methods allow one to track the whole Pareto front rather than converging to a single non-dominated solution. We augmented an efficient hypervolume computation technique with hypervolume increment strategy, and established Lipschitzianity of the resulting objective function. We used two deterministic Lipschitz optimization methods together with the hypervolume objective and benchmarked them against some state-of-the-art alternative multiobjective optimization methods, establishing the competitiveness of the proposed approach.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/189101