Extended hesitant fuzzy linguistic term set with fuzzy confidence for solving group decision-making problems

This paper presents a new extension of the hesitant fuzzy linguistic term set (HFLTS) called intuitionistic fuzzy confidence-based HFLTS that associates an intuitionistic fuzzy value (IFV) with each linguistic term. The resulting term set is termed as intuitionistic fuzzy confidence hesitant fuzzy linguistic term set (IFCHFLTS). The previous studies on the linguistic decision making have emphasized little upon the preference and non-preference for each of the linguistic terms. This information, however, is crucial in multi-criteria decision making under uncertainty. In this regard, we find IFV particularly useful for qualifying each of the linguistic terms with the agent’s degree of preference, non-preference, and hesitation values. Besides, a new aggregation operator named intuitionistic fuzzy confidence linguistic simple weighted geometry (IFCLSWG) is also proposed to fuse decision makers’ linguistic preferences. Further, the criteria weights are estimated using a new method called intuitionistic fuzzy confidence linguistic standard variance. An approach is also suggested for ranking the given alternatives by adapting VIKOR under the proposed IFCHFLTS context. Finally, the practicality and usefulness of the proposal are demonstrated through two real-world problems in green supplier selection for manufacturing industry, and medical diagnosis. The strengths and weaknesses of the proposal are also highlighted by drawing upon a comparison with similar methods.

[1]  Zeshui Xu,et al.  Hesitant Fuzzy Linguistic VIKOR Method and Its Application in Qualitative Multiple Criteria Decision Making , 2015, IEEE Transactions on Fuzzy Systems.

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

[3]  Yin-Feng Xu,et al.  Consistency and consensus measures for linguistic preference relations based on distribution assessments , 2014, Inf. Fusion.

[4]  K. S. Ravichandran,et al.  A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences , 2017, Appl. Soft Comput..

[5]  Zeshui Xu,et al.  Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment , 2004, Inf. Sci..

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

[7]  Zeshui Xu,et al.  Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment , 2012, Inf. Fusion.

[8]  Carlos Henggeler Antunes,et al.  MCDA and Energy Planning , 2005 .

[9]  K. S. Ravichandran,et al.  Probabilistic Linguistic Preference Relation-Based Decision Framework for Multi-Attribute Group Decision Making , 2018, Symmetry.

[10]  K. S. Ravichandran,et al.  Solving cloud vendor selection problem using intuitionistic fuzzy decision framework , 2018, Neural Computing and Applications.

[11]  Chiang Kao,et al.  Weight determination for consistently ranking alternatives in multiple criteria decision analysis , 2010 .

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

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

[14]  Francisco Herrera,et al.  Hesitant Fuzzy Linguistic Term Sets for Decision Making , 2012, IEEE Transactions on Fuzzy Systems.

[15]  Francisco Herrera,et al.  A model of consensus in group decision making under linguistic assessments , 1996, Fuzzy Sets Syst..

[16]  C. Spearman.  The proof and measurement of association between two things. , 2015, International journal of epidemiology.

[17]  Mohsen Rostamy-Malkhalifeh,et al.  A Multi-Criteria Intuitionistic Fuzzy Group Decision Making Method for Supplier Selection with VIKOR Method , 2012, Int. J. Fuzzy Syst. Appl..

[18]  Manish Agarwal,et al.  Generalized intuitionistic fuzzy soft sets with applications in decision-making , 2013, Appl. Soft Comput..

[19]  Xiaolu Zhang,et al.  Probabilistic Linguistic VIKOR Method to Evaluate Green Supply Chain Initiatives , 2017 .

[20]  R. Venkata Rao,et al.  Industrial robot selection using a novel decision making method considering objective and subjective preferences , 2011, Robotics Auton. Syst..

[21]  M. Jin,et al.  A linguistic entropy weight method and its application in linguistic multi-attribute group decision making , 2016 .

[22]  Zeshui Xu,et al.  Probabilistic linguistic term sets in multi-attribute group decision making , 2016, Inf. Sci..

[23]  Zeshui Xu,et al.  Interactive algorithms for improving incomplete linguistic preference relations based on consistency measures , 2016, Appl. Soft Comput..

[24]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[25]  Dejian Yu,et al.  Mapping development of linguistic decision making studies , 2016, J. Intell. Fuzzy Syst..

[26]  Yucheng Dong,et al.  Multi-attribute group decision making methods with proportional 2-tuple linguistic assessments and weights , 2014, Int. J. Comput. Intell. Syst..

[27]  Adrião Duarte Dória Neto,et al.  Intuitionistic Fuzzy Probability , 2010, SBIA.

[28]  Chunfang Liu,et al.  Correlated aggregation operators for simplified neutrosophic set and their application in multi-attribute group decision making , 2015, J. Intell. Fuzzy Syst..

[29]  Francisco Herrera,et al.  Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule , 2018, IEEE Transactions on Fuzzy Systems.

[30]  Jan Johansson,et al.  Comprehensive Evaluation on Employee Satisfaction of Mine Occupational Health and Safety Management System Based on Improved AHP and 2-Tuple Linguistic Information , 2017 .

[31]  Francisco Herrera,et al.  Hesitant Fuzzy Linguistic Term Set and Its Application in Decision Making: A State-of-the-Art Survey , 2017, International Journal of Fuzzy Systems.

[32]  Francisco Herrera,et al.  A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach , 1995, Inf. Sci..

[33]  Sen Liu,et al.  Decision making for the selection of cloud vendor: An improved approach under group decision-making with integrated weights and objective/subjective attributes , 2016, Expert Syst. Appl..

[34]  Francisco Herrera,et al.  A linear programming method for multiple criteria decision making with probabilistic linguistic information , 2017, Inf. Sci..

[35]  T. Saaty,et al.  Why the magic number seven plus or minus two , 2003 .

[36]  Surapati Pramanik,et al.  TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment , 2014, Neural Computing and Applications.

[37]  Zhibin Wu,et al.  Possibility Distribution-Based Approach for MAGDM With Hesitant Fuzzy Linguistic Information , 2016, IEEE Transactions on Cybernetics.

[38]  Debashree Guha,et al.  Article in Press G Model Applied Soft Computing Partitioned Bonferroni Mean Based on Linguistic 2-tuple for Dealing with Multi-attribute Group Decision Making , 2022 .

[39]  Bin Gu,et al.  Incremental Support Vector Learning for Ordinal Regression , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[40]  Francisco Rodrigues Lima Junior,et al.  A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection , 2014, Appl. Soft Comput..

[41]  Zeshui Xu,et al.  Consistency of the fused intuitionistic fuzzy preference relation in group intuitionistic fuzzy analytic hierarchy process , 2015, Appl. Soft Comput..

[42]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .