q‐Rung orthopair uncertain linguistic partitioned Bonferroni mean operators and its application to multiple attribute decision‐making method

A q‐rung orthopair uncertain linguistic set can be served as an extension of an uncertain linguistic set (ULS) and a q‐rung orthopair fuzzy set, which can also be treated as a generalized form of the existing intuitionistic ULS and Pythagorean ULS. The new linguistic set uses the uncertain linguistic variable to express the qualitative evaluation information and allows decision makers to provide their true views freely in a larger membership grade space. In this paper, we investigate the Bonferroni mean under the q‐rung orthopair uncertain linguistic environment, then we propose the q‐rung orthopair uncertain linguistic Bonferroni mean and its weighted form. Furthermore, considering the specific partition pattern among the attributes, the q‐rung orthopair uncertain linguistic partitioned Bonferroni mean and its weighted form are developed. Meanwhile, we discuss several representative cases and attractive properties of our proposed operators in depth. Subsequently, a novel multi‐attribute decision‐making method is developed based on the above‐mentioned aggregation operators. In the end, a comprehensible case is performed to analyze the superiority of the developed method by comparing with other typical studies.

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

[2]  Peng Wang,et al.  Some q‐Rung Orthopair Fuzzy Aggregation Operators and their Applications to Multiple‐Attribute Decision Making , 2018, Int. J. Intell. Syst..

[3]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

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

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

[6]  Junqing Li,et al.  An Efficient Optimization Algorithm for Resource-Constrained Steelmaking Scheduling Problems , 2018, IEEE Access.

[7]  Peide Liu,et al.  Multiple attribute decision‐making method for dealing with heterogeneous relationship among attributes and unknown attribute weight information under q‐rung orthopair fuzzy environment , 2018, Int. J. Intell. Syst..

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

[9]  Yuyan Han,et al.  Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions , 2018 .

[10]  Ronald R. Yager,et al.  Generalized Orthopair Fuzzy Sets , 2017, IEEE Transactions on Fuzzy Systems.

[11]  Peide Liu,et al.  Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple attribute decision-making , 2017, Int. J. Syst. Sci..

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

[13]  Ronald R. Yager,et al.  Generalized Bonferroni mean operators in multi-criteria aggregation , 2010, Fuzzy Sets Syst..

[14]  Radko Mesiar,et al.  Extended Bonferroni Mean Under Intuitionistic Fuzzy Environment Based on a Strict t-Conorm , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[15]  Xin Zhang,et al.  Some intuitionistic uncertain linguistic Heronian mean operators and their application to group decision making , 2014, Appl. Math. Comput..

[16]  Zeshui Xu,et al.  Intuitionistic Fuzzy Bonferroni Means , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

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

[18]  Peide Liu,et al.  Pythagorean uncertain linguistic partitioned Bonferroni mean operators and their application in multi-attribute decision making , 2017, J. Intell. Fuzzy Syst..

[19]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[20]  Muhammad Irfan Ali,et al.  Another view on q‐rung orthopair fuzzy sets , 2018, Int. J. Intell. Syst..

[21]  Zeshui Xu,et al.  Interval‐valued Pythagorean fuzzy extended Bonferroni mean for dealing with heterogenous relationship among attributes , 2018, Int. J. Intell. Syst..

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

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

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

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

[26]  Song Wang,et al.  Multiple attribute group decision making based on q‐rung orthopair fuzzy Heronian mean operators , 2018, Int. J. Intell. Syst..

[27]  Ronald R. Yager,et al.  Pythagorean Membership Grades in Multicriteria Decision Making , 2014, IEEE Transactions on Fuzzy Systems.

[28]  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 .