TOPSIS in Generalized Intuitionistic Fuzzy Environment

The aim of this chapter is to investigate the multiple attribute decision making problems to a selected project with generalized intuitionistic fuzzy information in which the information about weights is completely known and the attributes values are taken from the generalized intuitionistic fuzzy environment. Here, we extend the technique for order performance by similarity to ideal solution (TOPSIS) for the generalized intuitionistic fuzzy data. In addition, obtained the concept of possibility degree of generalized intuitionistic fuzzy numbers and used to solve ranking alternative in multi-attribute decision making problems.

[1]  Yang Liu,et al.  An Approach to Solve Group-Decision-Making Problems With Ordinal Interval Numbers , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Madhumangal Pal,et al.  Intuitionistic Fuzzy Block Matrix and its Some Properties , 2012 .

[3]  Masuma Mammadova,et al.  Application of Fuzzy Optimization Method in Decision-Making for Personnel Selection , 2014 .

[4]  Zeshui Xu,et al.  Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making , 2007, Fuzzy Optim. Decis. Mak..

[5]  Xiao-hong Chen,et al.  Extension of the TOPSIS method based on prospect theory and trapezoidal intuitionistic fuzzy numbers for group decision making , 2014 .

[6]  A. K. Adak,et al.  Interval cut-set of interval-valued intuitionistic fuzzy sets , 2011 .

[7]  Francisco Herrera,et al.  Multiperson decision-making based on multiplicative preference relations , 2001, Eur. J. Oper. Res..

[8]  F. E. Boran.  An Integrated Intuitionistic Fuzzy Multi Criteria Decision Making Method for Facility Location Selection , 2011 .

[9]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[10]  C. Yeh.  A Problem‐based Selection of Multi‐attribute Decision‐making Methods , 2002 .

[11]  K. Atanassov.  New operations defined over the intuitionistic fuzzy sets , 1994 .

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  W. Cook,et al.  A multiple criteria decision model with ordinal preference data , 1991 .

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

[15]  Saralees Nadarajah,et al.  A new generalized intuitionistic fuzzy set , 2014 .

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

[17]  Thomy Eko Saputro,et al.  Supplier Selection Using Integrated Fuzzy TOPSIS and MCGP: A Case Study , 2014 .

[18]  Madhumangal Pal,et al.  Interval Cut-Set of Generalized Interval-Valued Intuitionistic Fuzzy Sets , 2012, Int. J. Fuzzy Syst. Appl..

[19]  V. Lakshmana Gomathi Nayagam,et al.  Multi-criteria decision-making method based on interval-valued intuitionistic fuzzy sets , 2011, Expert Syst. Appl..

[20]  Yong Beom Park,et al.  Generalized Intuitionistic Fuzzy Matrices , 2004 .

[21]  Madhumangal Pal,et al.  Some properties of generalized intuitionistic fuzzy nilpotent matrices over distributive lattice , 2012 .