Exponential operations for intuitionistic fuzzy numbers and interval numbers in multi-attribute decision making

2016 ◽  
Vol 16 (2) ◽  
pp. 183-204 ◽  
Author(s):  
Xunjie Gou ◽  
Zeshui Xu
2019 ◽  
Vol 11 (18) ◽  
pp. 5057 ◽  
Author(s):  
Ren-Jie Mao ◽  
Jian-Xin You ◽  
Chun-Yan Duan ◽  
Lu-Ning Shao

The third-party platform named ECO system is used by many transnational companies to monitor the sustainability performance of their global suppliers because of its easiness and shareability. Nonetheless, methods used in this platform for evaluating and calculating the sustainability performance of the alternative suppliers are criticized for their lack of accuracy. In response to these problems, this paper presents a heterogeneous multi-criteria decision-making (MCDM) method based on interval-valued intuitionistic fuzzy--an acronym in Portuguese for interactive multi-criteria decision making (IVIF--TODIM) to improve the efficiency of the evaluation model. Considering the varying features of evaluation criteria, i.e., either quantitative or qualitative, the evaluation values under different criteria are expressed in their appropriate information types. In this paper, a general method based on the relative closeness to the technique for order preference by similarity to ideal solution (TOPSIS) method is applied for aggregating the heterogeneous assessment information, including crisp numbers, interval numbers, and triangular fuzzy numbers (TFNs), into interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) is extended and employed to prioritize the alternative suppliers. Finally, the applicability and effectiveness of the proposed method is verified by a practical example of polymer manufacturing company and a comparison analysis with existing methods.


Author(s):  
SHU-PING WAN

Triangular intuitionistic fuzzy numbers (TIFNs) are a special case of intuitionistic fuzzy sets. The purpose of this paper is to develop a new decision making method based on possibility variance coefficient to solve the multi-attribute decision making (MADM) problems, in which the attribute values are in the form of TIFNs and the weight preference information is incomplete. The possibility mean, variance and standard deviation for a TIFN are introduced as well as the possibility variance coefficient. Hereby, a new method to rank TIFNs is given on the basis of the possibility variance coefficients. The bi-objective mathematical programming, which minimizes the possibility variance coefficients of membership and non-membership functions for alternative's overall attribute values, is constructed. Using the max-min method, two non-linear fractional programming models are transformed into the linear programming models through the Charnes and Cooper transformation. Thus, the Pareto optimal solution to the bi-objective mathematical programming can be derived by solving the single-objective programming model. The ranking order of alternatives is obtained according to the minimum possibility variance coefficients. A personal selection example is given to verify the developed method and to demonstrate its feasibility and effectiveness. The analysis of comparison with other method is also conducted.


2015 ◽  
Vol 3 (1) ◽  
pp. 86-96 ◽  
Author(s):  
Chunlin Luo ◽  
Xin Tian ◽  
Shuping Wan

AbstractHeavy ordered weighted averaging (OWA) operator is important for characterizing the decision maker’s attitudinal character in multi-attribute decision making (MADM) problem with part or total ignorance. This paper develops a new method based on heavy OWA operator to solve the MADM problem in which the attributes are characterized by some trapezoidal intuitionistic fuzzy numbers (TrIFNs). TrIFN, as a special kind of intuitionistic fuzzy set defined on the real numbers, is useful for characterizing the ill-known quantity in reality. Firstly, the operation laws and the cut sets concept for TrIFNs are introduced. Then the authors define the membership and non-membership average indexes. A new ranking method is developed on the basis of the two indexes. In the proposed decision model, the multi-attribute TrIFN values of the candidates are aggregated by the Heavy OWA operator, and ranked by their membership and non-membership average indexes. Lastly, the authors illustrate the proposed method by a numerical example which implies the practicality and effectiveness of the method.


2021 ◽  
Author(s):  
Meishe Liang ◽  
Ju-Sheng Mi ◽  
Shaopu Zhang ◽  
Chenxia Jin

Abstract Ranking intuitionistic fuzzy numbers is an important issue in practical application of intuitionistic fuzzy sets. For making a rational decision, people need to get an effective sorting over the set of intuitionistic fuzzy numbers. Many scholars rank intuitionistic fuzzy numbers by defining different measures. These measures do not comprehensively consider the fuzzy semantics expressed by membership degree, nonmembership degree and hesitancy degree of intuitionistic fuzzy numbers. As a result, the ranking results are often counterintuitive, such as the indifference problems, the non-robustness problems, etc. In this paper, according to geometrical representation, a novel measure for intuitionistic fuzzy number is defined, which is called the ideal measure. After that a new sorting approach of intuitionistic fuzzy numbers is proposed. It is proved that the intuitionistic fuzzy order obtained by the ideal measure satisfies the properties of weak admissibility, membership degree robustness, nonmembership degree robustness, and determinism. Numerical example is applied to illustrate the effectiveness and feasibility of this method. Finally, using the presented approach, the optimal alternative can be acquired in multi-attribute decision making problem. Comparison analysis shows that the intuitionistic fuzzy value ordering method obtained by the ideal measure is more effectiveness and simplicity than other existing methods.


2010 ◽  
Vol 44-47 ◽  
pp. 1075-1079
Author(s):  
Liang Zhong Shen ◽  
Guang Bo Li ◽  
Wen Bin Liu

This paper has summarized the current ranking method for interval-valued intuitionistic fuzzy numbers, and then through the introduction of decision-makers’ mentality indicator, presented a new ranking method for interval-valued intuitionistic fuzzy numbers based on mentality function. Not only the nature of mentality function is deeply discussed but also the decision-making model based on the interval-valued intuitionistic fuzzy numbers is constructed. At last, an example is illustrated to prove the model's accuracy and effectiveness.


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