Intuitionistic fuzzy multiple attribute group decision making based on projection method

In decision making problems there may be cases in which decision makers do not have an in-depth knowledge of the problem to be solved. In such cases, more and more research has been conducted within a fuzzy or intuitionistic fuzzy framework. In this paper, we investigate the group decision making problems in which all the evaluation information provided by the decision makers is characterized by intuitionistic fuzzy decision matrices where each of the elements is expressed as intuitionistic fuzzy numbers (IFNs), and both weights of attributes and decision makers weights are incompletely known, which may be constructed by IFNs. By employing a projection model, fractional programming models are developed to determine the closeness interval values of alternatives. The interval values are subsequently used to aggregate into an overall interval value for each alternative, and the likelihood is applied to ranking and selection of alternatives. Feasibility and effectiveness of the developed models are illustrated with an example of investment decision problem.

[1]  Anna Pankowska,et al.  General IF-sets with triangular norms and their applications to group decision making , 2006, Inf. Sci..

[2]  Zeshui Xu,et al.  Projection Method For Uncertain Multi-Attribute Decision Making With Preference Information On Alternatives , 2004, Int. J. Inf. Technol. Decis. Mak..

[3]  Shu Liu,et al.  Fractional programming methodology for multi-attribute group decision-making using IFS , 2009, Appl. Soft Comput..

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

[5]  Janusz Kacprzyk,et al.  A concept of similarity for intuitionistic fuzzy sets and its use in group decision making , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[6]  Zeshui Xu,et al.  Intuitionistic preference relations and their application in group decision making , 2007, Inf. Sci..

[7]  Francisco Herrera,et al.  Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[8]  Janusz Kacprzyk,et al.  Using intuitionistic fuzzy sets in group decision making , 2002 .

[9]  Francisco Herrera,et al.  Linguistic decision analysis: steps for solving decision problems under linguistic information , 2000, Fuzzy Sets Syst..

[10]  Zeshui Xu,et al.  Some geometric aggregation operators based on intuitionistic fuzzy sets , 2006, Int. J. Gen. Syst..

[11]  Dug Hun Hong,et al.  Multicriteria fuzzy decision-making problems based on vague set theory , 2000, Fuzzy Sets Syst..

[12]  Francisco Herrera,et al.  Fuzzy Sets and Their Extensions: Representation, Aggregation and Models , 2008 .

[13]  Janusz Kacprzyk,et al.  A consensus‐reaching process under intuitionistic fuzzy preference relations , 2003, Int. J. Intell. Syst..

[14]  Francisco Herrera,et al.  Fuzzy Sets and Their Extensions: Representation, Aggregation and Models - Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision , 2007, Fuzzy Sets and Their Extensions: Representation, Aggregation and Models.

[15]  Ronald R. Yager,et al.  Intuitionistic fuzzy interpretations of multi-criteria multi-person and multi-measurement tool decision making , 2005, Int. J. Syst. Sci..

[16]  Xu Ze.  Algorithm for priority of fuzzy complementary judgement matrix , 2001 .

[17]  Humberto Bustince,et al.  Vague sets are intuitionistic fuzzy sets , 1996, Fuzzy Sets Syst..

[18]  Shyi-Ming Chen,et al.  Handling multicriteria fuzzy decision-making problems based on vague set theory , 1994 .

[19]  Zhoujing Wang,et al.  Multi-attribute decision making models and methods under interval-valued intuitionistic fuzzy environment , 2008, 2008 Chinese Control and Decision Conference.