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dc.contributor.authorGong, Zaiwuen
dc.contributor.authorZhang, Ningen
dc.contributor.authorChiclana, Franciscoen
dc.date.accessioned2018-08-16T13:40:12Z
dc.date.available2018-08-16T13:40:12Z
dc.date.issued2018-07-20
dc.identifier.citationGong, Z., Zhang, N. and Chiclana, F. (2018) The Optimization Ordering Model for Intuitionistic Fuzzy Preference Relations with Utility Functions. Knowledge-Based Systems,162, pp. 174-184en
dc.identifier.urihttp://hdl.handle.net/2086/16482
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractIntuitionistic fuzzy sets describe information from the three aspects of membership degree, non-membership degree and hesitation degree, which has more practical significance when uncertainty pervades qualitative decision problems. In this paper, we investigate the problem of ranking intuitionistic fuzzy preference relations (IFPRs) based on various non-linear utility functions. First, we transform IFPRs into their isomorphic interval-value fuzzy preference relations (IVFPRs), and utilise non-linear utility functions, such as parabolic, S-shaped, and hyperbolic absolute risk aversion, to fit the true value of a decision-maker's judgement. Ultimately, the optimization ordering models for the membership and non-membership of IVFPRs based on utility function are constructed, with objective function aiming at minimizing the distance deviation between the multiplicative consistency ideal judgment and the actual judgment, represented by utility function, subject to the decision-maker's utility constraints. The proposed models ensure that more factual and optimal ranking of alternative is acquired, avoiding information distortion caused by the operations of intervals. Second, by introducing a non-Archimedean infinitesimal, we establish the optimization ordering model for IFPRs with the priority of utility or deviation, which realises the goal of prioritising solutions under multi-objective programming. Subsequently, we verify that a close connection exists between the ranking for membership and non-membership degree IVFPRs. Comparison analyses with existing approaches are summarized to demonstrate that the proposed models have advantage in dealing with group decision making problems with IFPRs.en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectIntuitionistic fuzzy preference relationen
dc.subjectUtility Functionen
dc.subjectRankingen
dc.subjectMultiplicative consistencyen
dc.subjectNon-archimedean infinitesimalen
dc.titleThe Optimization Ordering Model for Intuitionistic Fuzzy Preference Relations with Utility Functionsen
dc.typeArticleen
dc.identifier.doihttps://dx.doi.org/10.1016/j.knosys.2018.07.012
dc.researchgroupInstitute of Artificial Intelligence (IAI)en
dc.peerreviewedYesen
dc.funderThis research is partially supported by the National Natural Science Foundation of China (Grant \#: 71171115, 71571104), the Reform Foundation of Postgraduate Education and Teaching in Jiangsu Province (Grant \#: JGKT10034), a Six Talent Peaks Project in Jiangsu Province (Grant \#: 2014-JY-014), Top-notch Academic Programs Project of Jiangsu Higher Education Institutions, and the Postgraduate Research \& Practice Innovation Program of Jiangsu Province (KYCX17\_0904).en
dc.projectidThis research is partially supported by the National Natural Science Foundation of China (Grant \#: 71171115, 71571104), the Reform Foundation of Postgraduate Education and Teaching in Jiangsu Province (Grant \#: JGKT10034), a Six Talent Peaks Project in Jiangsu Province (Grant \#: 2014-JY-014), Top-notch Academic Programs Project of Jiangsu Higher Education Institutions, and the Postgraduate Research \& Practice Innovation Program of Jiangsu Province (KYCX17\_0904).en
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2018-07-04en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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