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New Fuzzy Preference Relations and its Application in Group Decision Making
Abstract:Decision making preferences to certain criteria usually focus on positive degrees without considering the negative degrees. However, in real life situation, evaluation becomes more comprehensive if negative degrees are considered concurrently. Preference is expected to be more effective when considering both positive and negative degrees of preference to evaluate the best selection. Therefore, the aim of this paper is to propose the conflicting bifuzzy preference relations in group decision making by utilization of a novel score function. The conflicting bifuzzy preference relation is obtained by introducing some modifications on intuitionistic fuzzy preference relations. Releasing the intuitionistic condition by taking into account positive and negative degrees simultaneously and utilizing the novel score function are the main modifications to establish the proposed preference model. The proposed model is tested with a numerical example and proved to be simple and practical. The four-step decision model shows the efficiency of obtaining preference in group decision making.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330111Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1270
 Atanassov K., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 110(1986) 87 - 96.
 Abu Osman M.T., Conflicting bifuzzy evaluation, Proceeding and Mathematics Symposium (CSMS06). Kolej Universiti Sains dan Teknologi Malaysia, Kuala Terengganu, Malaysia (8 - 9 Nov 2006) In Malay.
 Deschrijver, G. and Kerre, E. E., 2007, On the position of intuitionistic fuzzy set theory in the framework of theories modeling imprecision, Information Sciences, Accepted Manuscript, doi: 10.1016/j.ins.2007.03.019 (Printed on May 21, 2007)
 Gianpiero C. and David C., Basic intuitionistic principle in fuzzy set theories and its extension (A terminological debate on Atanassov IFS), Fuzzy Sets and System, 157(2006) 3198 - 3219.
 Herrera, E. Chicl by applying on ana, F., Herrera, F. , Alonso, S. (in press) . A Group decision making model with incomplete fuzzy preference relations based on additive consistency, IEEE Transactions on System, Man and Cybernetics-Part B.
 Hong D. J. and Choi C. H., Multiciretia fuzzy decisioan - making problems based on vague set theory, Fuzzy Sets and Systems, 114(2000) 103 - 113.
 Imran, et.al. (2008). A new condition for conflicting bifuzzy sets based on intuitionistic evaluation, International Journal of Computational and Mathematical Sciences, 2(4), 161-165.
 Przemyslaw G. and Edyta M., Some notes on (Atanassov-s) intuitionistic fuzzy sets, Fuzzy Sets and System, 156(2005) 492 - 495.
 Saaty TH. L., The Analytic Hierarchy Process (McGraw - Hill, New York, 1980)
 Szmidt E., Kacprzyk J., Group Decision Making under intuitionistic fuzzy preference relations, in: Proceeding of 7th IPMU Conference, Paris (1998), pp. 172 - 178.
 Scmidt, E. Kacprzyk. J, (2002). Using intuitionistic fuzzy sets in group decision making, Control and Cybernetics 31, 1037-1053.
 Tadeusz G. and Jacek M., Bifuzzy probabilistic sets, Fuzzy Sets and Systems, 71(1995) 207 - 214.
 Tamalika C. and Raya A.K., A new measure using intuitionistic fuzzy set theory and its application to edge detection, Applied Soft Computing, xxx(2007) xxx-xxx.
 Wang J., Zhang J, and Liu S.Y., A new score function for fuzzy MCDM based on vague set theory, International Journal of Computational Cognition, Vol. 4, No. 1, (2006)
 Xu Z.S., Intuitionistic preference relations and their application in group decision making, Information Sciences, 177 (2007) 2363 - 2379.
 Zadeh L. A., Fuzzy Sets, Information and Control, 8(1965) 338 - 353.
 Zamali T., Lazim Abdullah M., Abu Osman, M.T. (2008). An introduction to conflicting bifuzzy set theory, International Journal of Mathematics and Statistics, 3(8), 86 - 95, (ISSN 0973 - 8347).
 Zamali T., A novel linguistic aggregation method for group decision making, The 3rd International Conference on Mathematics and Statistics (ICoMS-3) Institut Pertanian Bogor, Indonesia, 5-6 August (2008).
 Zhang, W. R. and Zhang, L., 2004, Yin Yang bipolar logic and bipolar fuzzy logic, Information Sciences, 165, 265 - 287.