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dc.contributor.authorLi, Longmeien
dc.contributor.authorYevseyeva, Irynaen
dc.contributor.authorTrautmann, H.en
dc.contributor.authorJing, N.en
dc.contributor.authorEmmerich, M. T. M.en
dc.date.accessioned2017-04-03T15:13:26Z
dc.date.available2017-04-03T15:13:26Z
dc.date.issued2017-03-19
dc.identifier.citationLi, L., Yevseyeva, I., Basto-Fernandes, V., Trautmann, H., Jing, N. and Emmerich, M. (2017) Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms. In: Trautmann H. et al. (eds) Proceedings of Evolutionary Multi-Criterion Optimization: 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017. Lecture Notes in Computer Science, vol 10173. Springer, Cham. Pp. pp 406-421en
dc.identifier.urihttp://hdl.handle.net/2086/13996
dc.description.abstractIntegrating user preferences in Evolutionary Multiobjective Optimization (EMO) is currently a prevalent research topic. There is a large variety of preference handling methods (originated from Multicriteria decision making, MCDM) and EMO methods, which have been combined in various ways. This paper proposes a Web Ontology Language (OWL) ontology to model and systematize the knowledge of preference-based multiobjective evolutionary algorithms (PMOEAs). Detailed procedure is given on how to build and use the ontology with the help of Protégé. Different use-cases, including training new learners, querying and reasoning are exemplified and show remarkable benefit for both EMO and MCDM communities.en
dc.language.isoenen
dc.publisherSpringeren
dc.titleBuilding and using an ontology of preference-based multiobjective evolutionary algorithms.en
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-319-54157-0_28
dc.researchgroupCyber Security Centreen
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2017-02-19en
dc.researchinstituteCyber Technology Institute (CTI)en


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