3-Objective Pareto Optimization for Problems with Chance Constraints

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dc.contributor.authorNeumann, F.
dc.contributor.authorWitt, C.
dc.contributor.conferenceGenetic and Evolutionary Computation Conference (GECCO) (15 Jul 2023 - 19 Jul 2023 : Lisbon, Portugal)
dc.contributor.editorPaquete, L.
dc.date.issued2023
dc.description.abstractEvolutionary multi-objective algorithms have successfully been used in the context of Pareto optimization where a given constraint is relaxed into an additional objective. In this paper, we explore the use of 3-objective formulations for problems with chance constraints. Our formulation trades off the expected cost and variance of the stochastic component as well as the given deterministic constraint. We point out benefits that this 3-objective formulation has compared to a bi-objective one recently investigated for chance constraints with Normally distributed stochastic components. Our analysis shows that the 3-objective formulation allows to compute all required trade-offs using 1-bit flips only, when dealing with a deterministic cardinality constraint. Furthermore, we carry out experimental investigations for the chance constrained dominating set problem and show the benefit for this classical NP-hard problem.
dc.description.statementofresponsibilityFrank Neumann, Carsten Witt
dc.identifier.citationProceedings of the Genetic and Evolutionary Computation Conference (GECCO '23), 2023 / Paquete, L. (ed./s), vol.abs/2304.08774, pp.731-739
dc.identifier.doi10.1145/3583131.3590392
dc.identifier.isbn9798400701191
dc.identifier.orcidNeumann, F. [0000-0002-2721-3618]
dc.identifier.urihttps://hdl.handle.net/2440/139306
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.publisher.placeNew York, NY
dc.relation.granthttp://purl.org/au-research/grants/arc/FT200100536
dc.rights© 2023 by the Association for Computing Machinery, Inc. (ACM).
dc.source.urihttps://dl.acm.org/doi/proceedings/10.1145/3583131
dc.subjectChance constraints; evolutionary multi-objective optimization; theory; runtime analysis
dc.title3-Objective Pareto Optimization for Problems with Chance Constraints
dc.typeConference paper
pubs.publication-statusPublished

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