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dc.contributor.authorEverson, Richard M.
dc.contributor.authorWalker, David J.
dc.contributor.authorFieldsend, Jonathan E.
dc.date.accessioned2014-04-22T12:19:06Z
dc.date.issued2013-07
dc.description.abstractMulti-objective optimisation yields an estimated Pareto front of mutually non-dominating solutions, but with more than three objectives understanding the relationships between solutions is challenging. Natural solutions to use as landmarks are those lying near to the edges of the mutually non-dominating set. We propose four definitions of edge points for many-objective mutually non-dominating sets and examine the relations between them. The first defines edge points to be those that extend the range of the attainment surface. This is shown to be equivalent to finding points which are not dominated on projection onto subsets of the objectives. If the objectives are to be minimised, a further definition considers points which are not dominated under maximisation when projected onto objective subsets. A final definition looks for edges via alternative projections of the set. We examine the relations between these definitions and their efficacy for synthetic concave- and convex-shaped sets, and on solutions to a prototypical many-objective optimisation problem, showing how they can reveal information about the structure of the estimated Pareto front.en_GB
dc.identifier.citationProceedings of the 15th annual conference on Genetic and Evolutionary Computation (GECCO ’13), pp. 607-614en_GB
dc.identifier.doi10.1145/2463372.2463452
dc.identifier.urihttp://hdl.handle.net/10871/14760
dc.language.isoenen_GB
dc.publisherACMen_GB
dc.relation.urlhttp://dx.doi.org/10.1145/2463372.2463452en_GB
dc.subjectmutually non-dominating setsen_GB
dc.subjectmany-objective optimisationen_GB
dc.subjectvisualisationen_GB
dc.subjectedgeen_GB
dc.subjectextremaen_GB
dc.titleEdges of Mutually Non-dominating Setsen_GB
dc.typeArticleen_GB
dc.typeConference paperen_GB
dc.date.available2014-04-22T12:19:06Z
dc.identifier.isbn9781450319638
dc.descriptionCopyright © 2013 ACM. This is the accepted, peer-reviewed version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 15th annual conference on Genetic and Evolutionary Computation (GECCO ’13), pp. 607-614, http://dx.doi.org/10.1145/2463372.2463452en_GB
dc.description15th annual conference on Genetic and Evolutionary Computation (GECCO ’13), Amsterdam, The Netherlands, 6-10 July 2013en_GB
dc.descriptionNotes: Won the Best Paper Award in the EMO tracken_GB


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