Ranking Interval-Valued Fuzzy Numbers with Intuitionistic Fuzzy Possibility Degree and Its Application to Fuzzy Multi-Attribute Decision Making

In this paper, we present the concept of intuitionistic fuzzy possibility degree (IFPD) for ranking interval-valued fuzzy numbers. This method overcomes the shortcomings of the previous techniques by giving the possibility degree in the form of intuitionistic fuzzy value, which contains positive degree, negative degree, and hesitant degree to compare any two intervals. The prominent characteristic of this method is that it can deal with the incomparable cases effectively, i.e., the two interval numbers have the same center or one interval number is nested in another one. As an application of the proposed method, a fuzzy multi-attribute decision-making method based on the IFPD is studied. Finally, we use a numerical example of selecting a laptop to illustrate the application of the proposed method.

[1]  G. P. Liu,et al.  A nonlinear interval number programming method for uncertain optimization problems , 2008, Eur. J. Oper. Res..

[2]  Vladik Kreinovich,et al.  On-line algorithms for computing mean and variance of interval data, and their use in intelligent systems , 2007, Inf. Sci..

[3]  Ulrich Bodenhofer Orderings of fuzzy sets based on fuzzy orderings. Part I: the basic approach , 2008, SOCO 2008.

[4]  M. Gorzałczany A method for inference in approximate reasoning based on interval-valued fuzzy sets , 1987 .

[5]  Miroslav Ciric,et al.  Reduction of fuzzy automata by means of fuzzy quasi-orders , 2011, Inf. Sci..

[6]  Yejun Xu,et al.  The induced generalized aggregation operators for intuitionistic fuzzy sets and their application in group decision making , 2012, Appl. Soft Comput..

[7]  G. Facchinetti,et al.  Note on ranking fuzzy triangular numbers , 1998 .

[8]  Mitsuo Gen,et al.  Order Relation between Intervals and Its Application to Shortest Path Problem , 1994 .

[9]  Ulrich Bodenhofer,et al.  Orderings of Fuzzy Sets Based on Fuzzy Orderings Part II: Generalizations , 2008, SOCO 2008.

[10]  F. Hosseinzadeh Lotfi,et al.  Using Monte Carlo method for ranking interval data , 2008, Appl. Math. Comput..

[11]  Zeshui Xu,et al.  Intuitionistic Fuzzy Aggregation Operators , 2007, IEEE Transactions on Fuzzy Systems.

[12]  Tsau Young Lin,et al.  Combination of interval-valued fuzzy set and soft set , 2009, Comput. Math. Appl..

[13]  Hülya Behret,et al.  Group decision making with intuitionistic fuzzy preference relations , 2014, Knowl. Based Syst..

[14]  Dorota Kuchta,et al.  A concept of the optimal solution of the transportation problem with fuzzy cost coefficients , 1996, Fuzzy Sets Syst..

[15]  Sukhamay Kundu,et al.  Min-transitivity of fuzzy leftness relationship and its application to decision making , 1997, Fuzzy Sets Syst..

[16]  Lan Shu,et al.  Generalized Interval-Valued Fuzzy Rough Set and its Application in Decision Making , 2015, Int. J. Fuzzy Syst..

[17]  Debjani Chakraborty,et al.  Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming , 2001, Fuzzy Sets Syst..

[18]  Yozo Nakahara,et al.  On the linear programming problems with interval coefficients , 1992 .

[19]  Yejun Xu,et al.  Incomplete interval fuzzy preference relations for supplier selection in supply chain management , 2014 .

[20]  Yuan-Chun Jiang,et al.  A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems , 2011, J. Syst. Softw..

[21]  Chee Peng Lim,et al.  A new method for ranking fuzzy numbers and its application to group decision making , 2014 .

[22]  Zeshui Xu,et al.  A survey of approaches to decision making with intuitionistic fuzzy preference relations , 2015, Knowl. Based Syst..

[23]  Peng Song,et al.  A two-grade approach to ranking interval data , 2012, Knowl. Based Syst..

[24]  Yejun Xu,et al.  Weak transitivity of interval-valued fuzzy relations , 2014, Knowl. Based Syst..

[25]  Francisco Chiclana,et al.  Non-dominance and attitudinal prioritisation methods for intuitionistic and interval-valued intuitionistic fuzzy preference relations , 2012, Expert Syst. Appl..

[26]  Etienne Kerre,et al.  A fuzzy ordering on multi-dimensional fuzzy sets induced from convex cones , 2002, Fuzzy Sets Syst..

[27]  Tapan Kumar Pal,et al.  On comparing interval numbers , 2000, Eur. J. Oper. Res..

[28]  Gwo-Hshiung Tzeng,et al.  Improving Mobile Commerce Adoption Using a New Hybrid Fuzzy MADM Model , 2015, Int. J. Fuzzy Syst..

[29]  S. Chanas,et al.  Multiobjective programming in optimization of interval objective functions -- A generalized approach , 1996 .

[30]  Dug Hun Hong,et al.  Some algebraic properties and a distance measure for interval-valued fuzzy numbers , 2002, Inf. Sci..

[31]  Yejun Xu,et al.  A distance-based aggregation approach for group decision making with interval preference orderings , 2014, Comput. Ind. Eng..

[32]  V. Lakshmana Gomathi Nayagam,et al.  A complete ranking of incomplete interval information , 2014, Expert Syst. Appl..

[33]  Lotfi A. Zadeh,et al.  Similarity relations and fuzzy orderings , 1971, Inf. Sci..

[34]  Janusz Kacprzyk,et al.  Distances between intuitionistic fuzzy sets , 2000, Fuzzy Sets Syst..

[35]  Xiang Li,et al.  The optimal interval combination forecasting model based on closeness degree and IOWHA operator under the uncertain environment , 2011, Grey Syst. Theory Appl..

[36]  Yejun Xu,et al.  Consistency test and weight generation for additive interval fuzzy preference relations , 2013, Soft Computing.

[37]  Branimir Seselja,et al.  Fuzzy relational inequalities and equations, fuzzy quasi-orders, closures and openings of fuzzy sets , 2015, Fuzzy Sets Syst..

[38]  S. Ovchinnikov Similarity relations, fuzzy partitions, and fuzzy orderings , 1991 .

[39]  B. Farhadinia,et al.  Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets , 2013, Inf. Sci..

[40]  Zeshui Xu,et al.  Priorities of Intuitionistic Fuzzy Preference Relation Based on Multiplicative Consistency , 2014, IEEE Transactions on Fuzzy Systems.

[41]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[42]  Guiwu Wei,et al.  Approaches to Interval Intuitionistic Trapezoidal Fuzzy Multiple Attribute Decision Making with Incomplete Weight Information , 2015, International Journal of Fuzzy Systems.

[43]  H. Ishibuchi,et al.  Multiobjective programming in optimization of the interval objective function , 1990 .

[44]  Yejun Xu,et al.  IFWA and IFWGM Methods for MADM under Atanassov's Intuitionistic Fuzzy Environment , 2015, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[45]  Ting-Yu Chen Multiple criteria group decision-making with generalized interval-valued fuzzy numbers based on signed distances and incomplete weights , 2012 .

[46]  W. Yao,et al.  The basic properties of some typical systems’ reliability in interval form , 2008 .

[47]  Zeshui Xu A Deviation-Based Approach to Intuitionistic Fuzzy Multiple Attribute Group Decision Making , 2010 .

[48]  J. Merigó,et al.  Interval-Valued Multiplicative Intuitionistic Fuzzy Preference Relations , 2013 .

[49]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[50]  Saeid Abbasbandy,et al.  A new approach for ranking of trapezoidal fuzzy numbers , 2009, Comput. Math. Appl..

[51]  Naoyuki Tamura,et al.  VSOP fuzzy numbers and their fuzzy ordering , 1998, Fuzzy Sets Syst..

[52]  Ramon E. Moore Methods and applications of interval analysis , 1979, SIAM studies in applied mathematics.

[53]  Jian-Bo Yang,et al.  A preference aggregation method through the estimation of utility intervals , 2005, Comput. Oper. Res..

[54]  Zeshui Xu,et al.  Framework of Group Decision Making With Intuitionistic Fuzzy Preference Information , 2015, IEEE Transactions on Fuzzy Systems.

[55]  C. Granger,et al.  Interval forecasting. An analysis based upon ARCH-quantile estimators , 1989 .

[56]  Yejun Xu,et al.  Incomplete interval fuzzy preference relations and their applications , 2014, Comput. Ind. Eng..

[57]  Zeshui Xu,et al.  Multiplicative consistency of interval-valued intuitionistic fuzzy preference relation , 2014, J. Intell. Fuzzy Syst..

[58]  Xiaoping Li,et al.  Correlation and information energy of interval-valued fuzzy numbers , 1999, Fuzzy Sets Syst..

[59]  Zeshui Xu,et al.  Intuitionistic Fuzzy Analytic Hierarchy Process , 2014, IEEE Transactions on Fuzzy Systems.