An Approach to Interval-Valued Hesitant Fuzzy Multiattribute Group Decision Making Based on the Generalized Shapley-Choquet Integral

The purpose of this paper is to develop an approach to multiattribute group decision making under interval-valued hesitant fuzzy environment. To do this, this paper defines some new operations on interval-valued hesitant fuzzy elements, which eliminate the disadvantages of the existing operations. Considering the fact that elements in a set may be interdependent, two generalized interval-valued hesitant fuzzy operators based on the generalized Shapley function and the Choquet integral are defined. Then, some models for calculating the optimal fuzzy measures on the expert set and the ordered position set are established. Because fuzzy measures are defined on the power set, it makes the problem exponentially complex. To simplify the complexity of solving a fuzzy measure, models for the optimal 2-additive measures are constructed. Finally, an investment problem is offered to show the practicality and efficiency of the new method.

[1]  Xiaohong Chen,et al.  Induced intuitionistic fuzzy Choquet integral operator for multicriteria decision making , 2011, Int. J. Intell. Syst..

[2]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[3]  Qiang Zhang,et al.  Approaches to multiple-criteria group decision making based on interval-valued intuitionistic fuzzy Choquet integral with respect to the generalized λ-Shapley index , 2013, Knowl. Based Syst..

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

[5]  Qiang Zhang,et al.  Some uncertain generalized Shapley aggregation operators for multi-attribute group decision making , 2015, J. Intell. Fuzzy Syst..

[6]  J. Kacprzyk Decision-making in a fuzzy environment with fuzzy termination time , 1978 .

[7]  Zeshui Xu,et al.  Interval-valued hesitant preference relations and their applications to group decision making , 2013, Knowl. Based Syst..

[8]  Hamid R. Tizhoosh,et al.  Image thresholding using type II fuzzy sets , 2005, Pattern Recognit..

[9]  G. Wei,et al.  Extension of VIKOR method for decision making problem based on hesitant fuzzy set , 2013 .

[10]  Chris Cornelis,et al.  Implication in intuitionistic fuzzy and interval-valued fuzzy set theory: construction, classification, application , 2004, Int. J. Approx. Reason..

[11]  K. Atanassov Operators over interval valued intuitionistic fuzzy sets , 1994 .

[12]  Vicenç Torra,et al.  On hesitant fuzzy sets and decision , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[13]  Ting-Yu Chen,et al.  An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets , 2014, Inf. Sci..

[14]  Fanyong Meng,et al.  Interval-valued intuitionistic fuzzy multi-criteria group decision making based on cross entropy and 2-additive measures , 2015, Soft Comput..

[15]  Zeshui Xu,et al.  Choquet integrals of weighted intuitionistic fuzzy information , 2010, Inf. Sci..

[16]  G. Choquet Theory of capacities , 1954 .

[17]  M. Grabisch The application of fuzzy integrals in multicriteria decision making , 1996 .

[18]  Michel Grabisch,et al.  K-order Additive Discrete Fuzzy Measures and Their Representation , 1997, Fuzzy Sets Syst..

[19]  Zeshui Xu,et al.  On distance and correlation measures of hesitant fuzzy information , 2011, Int. J. Intell. Syst..

[20]  Erhan Bozdag,et al.  The selection of technology forecasting method using a multi-criteria interval-valued intuitionistic fuzzy group decision making approach , 2013, Comput. Ind. Eng..

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

[22]  Qiang Zhang,et al.  Multi-attribute decision analysis under a linguistic hesitant fuzzy environment , 2014, Inf. Sci..

[23]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[24]  Pavel V. Sevastjanov,et al.  A new approach to the rule-base evidential reasoning in the intuitionistic fuzzy setting , 2014, Knowl. Based Syst..

[25]  R. Yager Fuzzy decision making including unequal objectives , 1978 .

[26]  S. Orlovsky Decision-making with a fuzzy preference relation , 1978 .

[27]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[28]  Guiwu Wei,et al.  Hesitant fuzzy prioritized operators and their application to multiple attribute decision making , 2012, Knowl. Based Syst..

[29]  Humberto Bustince,et al.  On averaging operators for Atanassov's intuitionistic fuzzy sets , 2011, Inf. Sci..

[30]  Zeshui Xu,et al.  Hesitant fuzzy geometric Bonferroni means , 2012, Inf. Sci..

[31]  Guiwu Wei,et al.  Induced hesitant interval-valued fuzzy Einstein aggregation operators and their application to multiple attribute decision making , 2013, J. Intell. Fuzzy Syst..

[32]  J. H. Park,et al.  Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment , 2011 .

[33]  Guiwu Wei,et al.  Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making , 2013, Knowl. Based Syst..

[34]  Ting-Yu Chen,et al.  A multicriteria group decision-making approach based on interval-valued intuitionistic fuzzy sets: A comparative perspective , 2011, Expert Syst. Appl..

[35]  Fanyong Meng,et al.  Entropy and similarity measure of Atanassov’s intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures , 2014, Pattern Analysis and Applications.

[36]  Fanyong Meng,et al.  Interval‐Valued Intuitionistic Fuzzy Multiattribute Group Decision Making Based on Cross Entropy Measure and Choquet Integral , 2013, Int. J. Intell. Syst..

[37]  Krassimir T. Atanassov,et al.  Interval-Valued Intuitionistic Fuzzy Sets , 2019, Studies in Fuzziness and Soft Computing.

[38]  Sadaaki Miyamoto,et al.  Information clustering based on fuzzy multisets , 2003, Inf. Process. Manag..

[39]  Miin-Shen Yang,et al.  A similarity measure of intuitionistic fuzzy sets based on the Sugeno integral with its application to pattern recognition , 2012, Inf. Sci..

[40]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy sets , 2011, Inf. Sci..

[41]  Fanyong Meng,et al.  An Approach to Interval-Valued Hesitant Fuzzy Multi-Attribute Decision Making with Incomplete Weight Information Based on Hybrid Shapley Operators , 2014, Informatica.

[42]  Chen Wang,et al.  Correlation Coefficients of Interval‐Valued Hesitant Fuzzy Sets and Their Application Based on the Shapley Function , 2016, Int. J. Intell. Syst..

[43]  Ronald R. Yager,et al.  Multiple objective decision-making using fuzzy sets , 1977 .

[44]  Ting-Yu Chen,et al.  Optimistic and pessimistic decision making with dissonance reduction using interval-valued fuzzy sets , 2011, Inf. Sci..

[45]  Zeshui Xu,et al.  Generalized Prioritized Multicriteria Aggregation , 2013, Int. J. Intell. Syst..

[46]  Guiwu Wei,et al.  Hesitant Fuzzy Choquet Integral Aggregation Operators and Their Applications to Multiple Attribute Decision Making , 2012 .

[47]  Peide Liu,et al.  Methods for aggregating intuitionistic uncertain linguistic variables and their application to group decision making , 2012, Inf. Sci..

[48]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..

[49]  R. Yager ON THE THEORY OF BAGS , 1986 .

[50]  Qiang Zhang,et al.  The induced generalized interval-valued intuitionistic fuzzy hybrid Shapley averaging operator and its application in decision making , 2013, Knowl. Based Syst..

[51]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[52]  Jerry M. Mendel,et al.  Applications of Type-2 Fuzzy Logic Systems to Forecasting of Time-series , 1999, Inf. Sci..

[53]  Na Chen,et al.  Some Hesitant Fuzzy Aggregation Operators with Their Application in Group Decision Making , 2011, Group Decision and Negotiation.

[54]  Ahmad Makui,et al.  Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets , 2009, Appl. Soft Comput..

[55]  Krassimir T. Atanassov,et al.  Type-1 Fuzzy Sets and Intuitionistic Fuzzy Sets , 2017, Algorithms.

[56]  Xiao-hong Chen,et al.  Some interval-valued intuitionistic uncertain linguistic Choquet operators and their application to multi-attribute group decision making , 2014 .

[57]  Fanyong Meng,et al.  A hesitant fuzzy linguistic multi-granularity decision making model based on distance measures , 2015, J. Intell. Fuzzy Syst..

[58]  Na Chen,et al.  Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis , 2013 .

[59]  Ting-Yu Chen,et al.  The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making , 2013, Eur. J. Oper. Res..

[60]  Jean-Luc Marichal,et al.  The influence of variables on pseudo-Boolean functions with applications to game theory and multicriteria decision making , 2000, Discret. Appl. Math..

[61]  V. Torra,et al.  A framework for linguistic logic programming , 2010 .

[62]  Chunqiao Tan,et al.  A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS , 2011, Expert Syst. Appl..

[63]  Huibert Kwakernaak,et al.  Rating and ranking of multiple-aspect alternatives using fuzzy sets , 1976, Autom..

[64]  F. Meng,et al.  Generalized intuitionistic fuzzy hybrid Choquet averaging operators , 2013, Journal of Systems Science and Systems Engineering.

[65]  L. S. Shapley,et al.  17. A Value for n-Person Games , 1953 .