scholarly journals Behavioral risky hesitant fuzzy linguistic multiple attribute decision making with priority degree method

2021 ◽  
Author(s):  
Wangwang Yu ◽  
Xin Wang Liu
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Multiple Attribute Decision Making ◽  
Ranking Method ◽  
Average Operator ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Linguistic Term ◽  
Fuzzy Linguistic ◽  
Evaluation Information

Abstract In this paper, we propose a behavioral risky hesitant fuzzy linguistic multiple attribute decision making with priority degree method. First, we define a new ranking method for hesitant fuzzy linguistic term sets to compare the hesitant fuzzy linguistic evaluation information and the expectation. Second, we give a relative distance for the hesitant fuzzy linguistic term set to get the distance between the hesitant fuzzy linguistic evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to get interval individual prospect value. Forth, we apply the average operator to get interval comprehensive prospect value. Fifth, we define a priority degree method of interval number to rank interval comprehension prospect value. Based on the above steps, we give the solution of risky hesitant fuzzy linguistic multiple attribute decision making problem. Further, we use the example to illustrate the feasibility and rationality of this behavior method and the comparative analysis between the existing decision making method for the hesitant fuzzy linguistic term.

Behavioral Risky Multiple Attribute Decision Making with Interval Type-2 Fuzzy Ranking Method and TOPSIS Method

2021 ◽  
pp. 1-41
Author(s):  
Wangwang Yu ◽  
Xinwang Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Multiple Attribute Decision Making ◽  
Ranking Method ◽  
Topsis Method ◽  
Multiple Attribute ◽  
Fuzzy Ranking ◽  
Interval Type ◽  
Evaluation Information

Considering the decision maker’s psychological state will influence their evaluation result in the risky multi-attribute decision-making problem, and the uncertainty of evaluation information. In this paper, we will propose a behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. The interval type-2 fuzzy set is used to express the uncertainty of evaluation information, the prospect theory is applied to describe people’s psychological state in the processing of risk decision making. First, we define a new ranking method for interval type-2 fuzzy set to compare the interval type-2 fuzzy evaluation information and the expectation. Second, we give a relative distance for interval type-2 fuzzy set to get the distance between the interval type-2 fuzzy evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to obtain the comprehensive prospect value. Fourth, we use the improved TOPSIS method and the comprehensive prospect value to rank the alternatives. Based on the above-mentioned steps, we give the solution for risky interval type-2 fuzzy multiple attribute decision-making problem, which named as the behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. Finally, we use an example to show the rationality of this method.

scholarly journals Lexicographic Orders of Intuitionistic Fuzzy Values and Their Relationships

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 166 ◽  
Author(s):  
Feng Feng ◽  
Meiqi Liang ◽  
Hamido Fujita ◽  
Ronald Yager ◽  
Xiaoyan Liu
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Scalar Product ◽  
Multiple Attribute Decision Making ◽  
Benchmark Problem ◽  
Score Functions ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Risk Investment ◽  
Membership Score

Intuitionistic fuzzy multiple attribute decision making deals with the issue of ranking alternatives based on the decision information quantified in terms of intuitionistic fuzzy values. Lexicographic orders can serve as efficient and indispensable tools for comparing intuitionistic fuzzy values. This paper introduces a number of lexicographic orders by means of several measures such as the membership, non-membership, score, accuracy and expectation score functions. Some equivalent characterizations and illustrative examples are provided, from which the relationships among these lexicographic orders are ascertained. We also propose three different compatible properties of preorders with respect to the algebraic sum and scalar product operations of intuitionistic fuzzy values, and apply them to the investigation of compatible properties of various lexicographic orders. In addition, a benchmark problem regarding risk investment is further explored to give a comparative analysis of different lexicographic orders and highlight the practical value of the obtained results for solving real-world decision-making problems.

scholarly journals Dual Generalized Nonnegative Normal Neutrosophic Bonferroni Mean Operators and Their Application in Multiple Attribute Decision Making

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 201 ◽  
Author(s):  
Jiongmei Mo ◽  
Han-Liang Huang
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Information Aggregation ◽  
Multiple Attribute Decision Making ◽  
Ranking Method ◽  
Bonferroni Mean ◽  
Operational Laws ◽  
Multiple Attribute ◽  
Geometric Bonferroni Mean ◽  
Neutrosophic Number

For multiple attribute decision making, ranking and information aggregation problems are increasingly receiving attention. In a normal neutrosophic number, the ranking method does not satisfy the ranking principle. Moreover, the proposed operators do not take into account the correlation between any aggregation arguments. In order to overcome the deficiencies of the existing ranking method, based on the nonnegative normal neutrosophic number, this paper redefines the score function, the accuracy function, and partial operational laws. Considering the correlation between any aggregation arguments, the dual generalized nonnegative normal neutrosophic weighted Bonferroni mean operator and dual generalized nonnegative normal neutrosophic weighted geometric Bonferroni mean operator were investigated, and their properties are presented. Here, these two operators are applied to deal with a multiple attribute decision making problem. Example results show that the proposed method is effective and superior.

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