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IMPROVING CONSISTENCY EVALUATION IN FUZZY MULTI-ATTRIBUTE PAIRWISE COMPARISON-BASED DECISION-MAKING METHODS

    https://doi.org/10.1142/S0217595914500249Cited by:2 (Source: Crossref)

    A typical approach to handle the complexity of multi-faceted decision-making problems is to use multi-attribute decision-making (MADM) methods based on pairwise comparisons. Fuzzy set theory has also been employed to cope with the uncertainty and vagueness involved in conducting the comparisons between components of a decision model. An important issue regarding the reliability of the output is the consistency of pairwise comparisons provided by the decision maker(s). Using the MADM method developed by Lu et al. (2007) as a foundation, this paper proposes an algorithm for evaluating the consistency level of pairwise comparison matrices, where linguistic data are used. A crisp numeric scale has been introduced to consider the priority of linguistic data and to avoid the complexity of handling fuzzy calculations in consistency evaluation of pairwise comparison matrices. As an advantage, the proposed method of consistency evaluation is capable of assessing the degree of inconsistency among the pairwise comparisons. Therefore, the acceptance or rejection of the pairwise comparisons can be determined based on the desired degree of tolerance in accepting inconsistent judgments. An application of a revised MADM method is then demonstrated in a case study involving flood mitigation project selection in Australia.

    References

    • I.   Ali , W. D.   Cook and M.   Kress , Management Science   32 , 1642 ( 1986 ) . Crossref, Web of ScienceGoogle Scholar
    • A.   Arbel , European Journal of Operational Research   43 , 317 ( 1989 ) . Crossref, Web of ScienceGoogle Scholar
    • C. G. E.   Boender , J. G.   Graan and F. A.   Lootsma , Fuzzy Sets and Systems   29 , 133 ( 1989 ) . Crossref, Web of ScienceGoogle Scholar
    • D. Y.   Chang , European Journal of Operational Research   95 , 649 ( 1996 ) . Crossref, Web of ScienceGoogle Scholar
    • H.   Deng , International Journal of Approximate Reasoning   21 , 215 ( 1999 ) . Crossref, Web of ScienceGoogle Scholar
    • Gold Coast City Council website. Flood Mitigation Fact sheet. Available at http://www.goldcoast.qld.gov.au/attachment/flood_mitigation_infosheet_reduce_risk.pdf. Accessed on August 2009 . Google Scholar
    • Y. Y.   Guh , R. W.   Po and K. R.   Lou , International Journal of Information and Management Science   20 , 71 ( 2009 ) . Web of ScienceGoogle Scholar
    • P. T.   Harker and L. G.   Vargas , Management Science   33 , 1383 ( 1987 ) . Crossref, Web of ScienceGoogle Scholar
    • E.   Herrera-Viedma et al. , European Journal of Operational Research   154 , 98 ( 2004 ) . Crossref, Web of ScienceGoogle Scholar
    • D. S.   Hochbaum and A.   Levin , Management Science   52 , 1394 ( 2006 ) . Crossref, Web of ScienceGoogle Scholar
    • C.   Kahraman , Fuzzy Multi-Criteria Decision-Making: Theory and Applications with Recent Developments ( Springer Science+Business Media , New York, USA , 2008 ) . CrossrefGoogle Scholar
    • C.   Kahraman , Z.   Ulukan and E.   Tolga , A fuzzy weighted evaluation method using objective and subjective measures , International ICSC Symposium on Engineering of Intelligent Systems (EIS'98) ( University of La Laguna Tenerife , Spain , 1998 ) . Google Scholar
    • L. C.   Leung and D.   Cao , European Journal of Operational Research   124 , 102 ( 2000 ) . Crossref, Web of ScienceGoogle Scholar
    • F. A.   Lootsma , Mathematical Models for Decision Support , eds. H. J.   Greenberg et al. ( Springer-Verlag , New York, NY , 1988 ) . Google Scholar
    • F. A.   Lootsma , Journal of Multi-Criteria Decision Analysis   2 , 87 ( 1993 ) . CrossrefGoogle Scholar
    • J.   Lu et al. , Multi-Objective Group Decision Making: Methods, Software and Applications with Fuzzy Set Techniques ( Imperial College Press , London , 2007 ) . LinkGoogle Scholar
    • T. L.   Saaty , The Analytical Hierarchy Process ( McGraw-Hill , New York, NY , 1980 ) . Google Scholar
    • T. L.   Saaty and P. K.   Kearns , Analytical Planning: The Organization of Systems ( Pergamon Press , Oxford , 1985 ) . Google Scholar
    • A. A.   Salo and R. P.   Hämäläinen , European Journal of Operational Research   82 , 458 ( 1995 ) . Crossref, Web of ScienceGoogle Scholar
    • A. A.   Salo , Fuzzy Sets and Systems   84 , 21 ( 1996 ) . Crossref, Web of ScienceGoogle Scholar
    • E. Triantaphyllouet al., Journal of Multi-Criteria Decision Analysis 3(3), 133 (1994). CrossrefGoogle Scholar
    • P. J. M.   van Laarhoven and W.   Pedrycz , Fuzzy Sets and Systems   11 , 199 ( 1983 ) . Crossref, Web of ScienceGoogle Scholar
    • S. H.   Zanakis et al. , European Journal of Operational Research   107 , 507 ( 1998 ) . Crossref, Web of ScienceGoogle Scholar