Bidirectional projection measure of linguistic neutrosophic numbers and their application to multi-criteria group decision making

Abstract Linguistic neutrosophic numbers (LNNs) are an effective tool in describing the incomplete and indeterminate evaluation information by using three linguistic variables (LVs) to denote the truth-degree (TD), indeterminacy-degree (ID), and falsity-degree (FD), and the bidirectional projection measure has some advantages in dealing with multi-criteria group decision making (MCGDM) problems because it can consider both the distance and the included angle, but more importantly, it considers the bidirectional projection between each alternative and the ideal solution. In this paper, we define a new distance measure between two linguistic neutrosophic sets (LNSs), and build a model based on the maximum deviation to obtain fuzzy measure, further, we develop the bidirectional projection-based MCGDM method with LNNs in which a weight model based on fuzzy measure is proposed where the weights of evaluation criteria is partial unknown and the interactions among criteria are considered. Finally, we use some examples to verify the effectiveness of the proposed approach and demonstrate its advantages by comparing with some existing methods.

[1]  Jian-qiang Wang,et al.  Hesitant Uncertain Linguistic Z-Numbers and Their Application in Multi-criteria Group Decision-Making Problems , 2017, Int. J. Fuzzy Syst..

[2]  Michel Grabisch,et al.  Fuzzy Measures and Integrals , 1995 .

[3]  Jun Ye,et al.  Multiple Attribute Decision-Making Methods Based on the Expected Value and the Similarity Measure of Hesitant Neutrosophic Linguistic Numbers , 2017, Cognitive Computation.

[4]  Hao Wu,et al.  Evaluating Investment Risks of Metallic Mines Using an Extended TOPSIS Method with Linguistic Neutrosophic Numbers , 2017, Symmetry.

[5]  Peide Liu,et al.  Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean , 2014, Neural Computing and Applications.

[6]  Zeshui Xu,et al.  Group consistency and group decision making under uncertain probabilistic hesitant fuzzy preference environment , 2017, Inf. Sci..

[7]  Jun Ye,et al.  Cosine Measures of Linguistic Neutrosophic Numbers and Their Application in Multiple Attribute Group Decision-Making , 2017, Inf..

[8]  Zeshui Xu,et al.  The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment , 2014, Knowl. Based Syst..

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

[10]  Juan M. Corchado,et al.  Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods , 2017, Knowl. Based Syst..

[11]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[12]  Zhongliang Guan,et al.  Evaluation Research on the Quality of the Railway Passenger Service Based on the Linguistic Variables and the Improved PROMETHEE-II Method , 2009, J. Comput..

[13]  Gui-Wu Wei,et al.  GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting , 2010, Knowl. Based Syst..

[14]  Jun Ye,et al.  Bidirectional projection method for multiple attribute group decision making with neutrosophic numbers , 2015, Neural Computing and Applications.

[15]  Jun Ye,et al.  An extended TOPSIS method for multiple attribute group decision making based on single valued neutrosophic linguistic numbers , 2015, J. Intell. Fuzzy Syst..

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

[17]  Jun Ye,et al.  Simplified neutrosophic harmonic averaging projection-based method for multiple attribute decision-making problems , 2015, International Journal of Machine Learning and Cybernetics.

[18]  Francisco Herrera,et al.  A proposal for improving the accuracy of linguistic modeling , 2000, IEEE Trans. Fuzzy Syst..

[19]  Zeshui Xu,et al.  A consensus process for group decision making with probabilistic linguistic preference relations , 2017, Inf. Sci..

[20]  Bojan Srdjevic,et al.  Heuristic aggregation of individual judgments in AHP group decision making using simulated annealing algorithm , 2016, Inf. Sci..

[21]  Zeshui Xu,et al.  On Method for Uncertain Multiple Attribute Decision Making Problems with Uncertain Multiplicative Preference Information on Alternatives , 2005, Fuzzy Optim. Decis. Mak..

[22]  Jun Ye Single valued neutrosophic cross-entropy for multicriteria decision making problems , 2014 .

[23]  Yi Yang,et al.  Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making , 2016, Inf. Sci..

[24]  F. Smarandache A Unifying Field in Logics: Neutrosophic Logic. , 1999 .

[25]  Zeshui Xu,et al.  Dual hesitant fuzzy VIKOR method for multi-criteria group decision making based on fuzzy measure and new comparison method , 2017, Inf. Sci..

[26]  Francisco Herrera,et al.  Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its use to deal with hesitant unbalanced linguistic information , 2016, Inf. Sci..

[27]  Gui-Wu Wei,et al.  Maximizing deviation method for multiple attribute decision making in intuitionistic fuzzy setting , 2008, Knowl. Based Syst..

[28]  Li-Jun Yang,et al.  An extension of ELECTRE to multi-criteria decision-making problems with multi-hesitant fuzzy sets , 2015, Inf. Sci..

[29]  Jun Ye,et al.  Projection and bidirectional projection measures of single-valued neutrosophic sets and their decision-making method for mechanical design schemes , 2017, J. Exp. Theor. Artif. Intell..

[30]  Jun Ye,et al.  Multiple Attribute Group Decision-Making Method Based on Linguistic Neutrosophic Numbers , 2017, Symmetry.

[31]  Rajshekhar Sunderraman,et al.  Single Valued Neutrosophic Sets , 2010 .

[32]  Jun Ye,et al.  Linguistic Neutrosophic Cubic Numbers and Their Multiple Attribute Decision-Making Method , 2017, Inf..

[33]  Jun Ye,et al.  Multiple attribute decision-making method based on linguistic cubic variables , 2018, J. Intell. Fuzzy Syst..

[34]  Jun Ye,et al.  Bonferroni Mean Operators of Linguistic Neutrosophic Numbers and Their Multiple Attribute Group Decision-Making Methods , 2017, Inf..

[35]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[36]  H. Simon,et al.  Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. , 1959 .

[37]  Jun Ye,et al.  Symmetry Measures of Simplified Neutrosophic Sets for Multiple Attribute Decision-Making Problems , 2018, Symmetry.

[38]  Rodolfo Lourenzutti,et al.  A generalized TOPSIS method for group decision making with heterogeneous information in a dynamic environment , 2016, Inf. Sci..

[39]  Macarena Espinilla,et al.  FLINTSTONES: A fuzzy linguistic decision tools enhancement suite based on the 2-tuple linguistic model and extensions , 2014, Inf. Sci..

[40]  uan-juan Penga,et al.  An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets , 2014 .

[41]  Jun Ye,et al.  Linguistic neutrosophic uncertain numbers and their multiple attribute group decision-making method , 2019, J. Intell. Fuzzy Syst..