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dc.contributor.authorEmmerich, M. T. M.en
dc.contributor.authorDeutz, A.en
dc.contributor.authorYevseyeva, Irynaen
dc.date.accessioned2016-05-26T13:46:36Z
dc.date.available2016-05-26T13:46:36Z
dc.date.issued2015-09-15
dc.identifier.citationEmmerich, M.T.M., Deutz, A. and Yevseyeva, I. (2015) A Bayesian approach to portfolios selection in multicriteria group decision making. CENTERIS’15, 7th Conference of ENTERprise Information Systems. Procedia Computer Science, 64, pp. 993-1000en
dc.identifier.urihttp://hdl.handle.net/2086/12088
dc.description.abstractIn the a-posteriori approach to multicriteria decision making the idea is to first find a set of interesting (usually non-dominated) decision alternatives and then let the decision maker select among these. Often an additional demand is to limit the size of alternatives to a small number of solutions. In this case, it is important to state preferences on sets. In previous work it has been shown that independent normalization of objective functions (using for instance desirability functions) combined with the hypervolume indicator can be used to formulate such set-preferences. A procedure to compute and to maximize the probability that a set of solutions contains at least one satisfactory solution is established. Moreover, we extend the model to the scenario of multiple decision makers. For this we compute the probability that at least one solution in a given set satisfies all decision makers. First, the information required a-priori from the decision makers is considered. Then, a computational procedure to compute the probability for a single set to contain a solution, which is acceptable to all decision makers, is introduced. Thereafter, we discuss how the computational effort can be reduced and how the measure can be maximized. Practical examples for using this in database queries will be discussed, in order to show how this approach relates to applications.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectMulticriteria Decision Analysisen
dc.subjectMultiobjective Optimizationen
dc.subjectWeighted Hypervolume Indicatoren
dc.subjectDesirability Functionsen
dc.subjectSet Performance Indicatorsen
dc.subjectGroup Decision Makingen
dc.titleA Bayesian approach to portfolios selection in multicriteria group decision makingen
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1016/j.procs.2015.08.618
dc.researchgroupCyber Security Centreen
dc.peerreviewedYesen
dc.explorer.multimediaNoen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.projectidEP/K006568/1en
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2015-09-15en
dc.researchinstituteCyber Technology Institute (CTI)en


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