scholarly journals An Approach to Evaluating Enterprise Financial Performance Based on the Control Inheritance of Family Businesses with Intuitionistic Fuzzy Information

2014 ◽  
Vol 2014 ◽  
pp. 1-4
Author(s):  
Hui Liu
Keyword(s):  
Decision Making ◽  
Financial Performance ◽  
Multiple Attribute Decision Making ◽  
Family Businesses ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute

We investigate the multiple attribute decision making problems for evaluating the enterprise financial performance based on the control inheritance of family businesses with intuitionistic fuzzy information. We utilize the intuitionistic fuzzy Bonferroni mean (IFBM) operator to aggregate the intuitionistic fuzzy information corresponding to each alternative and get the overall value of enterprise financial performance and then rank the enterprises and select the most desirable one(s) by using the overall value of enterprise financial performance. Finally, an illustrative example for evaluating the enterprise financial performance based on the control inheritance of family businesses is given to verify the developed approach and to demonstrate its practicality and effectiveness.

scholarly journals Generalized Linguistic Hesitant Intuitionistic Fuzzy Hybrid Aggregation Operators

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Yang ◽  
Jiarong Shi ◽  
Yongfeng Pang
Keyword(s):  
Decision Making ◽  
Geometric Mean ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
New Method ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Special Cases

Some hybrid aggregation operators have been developed based on linguistic hesitant intuitionistic fuzzy information. The generalized linguistic hesitant intuitionistic fuzzy hybrid weighted averaging (GLHIFHWA) operator and the generalized linguistic hesitant intuitionistic fuzzy hybrid geometric mean (GLHIFHGM) operator are defined. Some special cases of the new aggregation operators are studied and many existing aggregation operators are special cases of the new operators. A new multiple attribute decision making method based on the new aggregation operators is proposed and a practical numerical example is presented to illustrate the feasibility and practical advantages of the new method.

Triangular Intuitionistic Fuzzy Multiple Attribute Decision Making and Their Applications to Risk Evaluation for Risk Investment Projects

2016 ◽  
Vol 13 (10) ◽  
pp. 7120-7124
Author(s):  
Hong Jin
Keyword(s):  
Decision Making ◽  
Risk Evaluation ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Investment Projects ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Risk Investment

In this paper, we investigate the multiple attribute decision making problems about risk evaluation for risk investment projects with triangular intuitionistic fuzzy information. Then, we proposed the triangular intuitionistic fuzzy Einstein weighted geometric (TIFEWG) operator, triangular intuitionistic fuzzy Einstein ordered weighted geometric (TIFEOWG) operator and triangular intuitionistic fuzzy Einstein hybrid geometric (TIFEHG) operator and we develop an approach to multiple attribute decision making with triangular intuitionistic fuzzy information. Finally, an illustrative example for evaluating the risk of the risk investment projects with triangular intuitionistic fuzzy information is given to verify the developed approach.

scholarly journals Hesitant Fuzzy Generalised Bonferroni Mean Operators Based on Archimedean Copula for Multiple-Attribute Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ju Wu ◽  
Fang Liu ◽  
Yuan Rong ◽  
Yi Liu ◽  
Chengxi Liu
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Information Fusion ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Archimedean Copula ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Operation Rules ◽  
Multiple Attribute

Information fusion is an important part of multiple-attribute decision-making, and aggregation operator is an important tool of decision information fusion. Integration operators in a variety of fuzzy information environments have a slight lack of consideration for the correlation between variables. Archimedean copula provides information fusion patterns that rely on the intrinsic relevance of information. This paper extends the Archimedean copula to the aggregation of hesitant fuzzy information. Firstly, the Archimedean copula is used to generate the operation rules of the hesitant fuzzy elements. Secondly, the hesitant fuzzy copula Bonferroni mean operator and hesitant fuzzy weighted copula Bonferroni mean operator are propounded, and several properties are proved in detail. Furthermore, a decision-making method based on the operators is proposed, and the specific decision steps are given. Finally, an example is presented to illustrate the practical advantages of the method, and the sensitivity analysis of the decision results with the change of parameters is carried out.

scholarly journals Intuitionistic Linguistic Weighted Bonferroni Mean Operator and Its Application to Multiple Attribute Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Peide Liu ◽  
Lili Rong ◽  
Yanchang Chu ◽  
Yanwei Li
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Linguistic Variables ◽  
Fuzzy Information ◽  
Linguistic Information ◽  
Bonferroni Mean ◽  
Multiple Attribute ◽  
Special Cases ◽  
The Individual

The intuitionistic linguistic variables are easier to describe the fuzzy information which widely exists in the real world, and Bonferroni mean can capture the interrelationship of the individual arguments. However, the traditional Bonferroni mean can only process the crisp number. In this paper, we will extend Bonferroni mean to the intuitionistic linguistic environment and propose a multiple attribute decision making method with intuitionistic linguistic information based on the extended Bonferroni mean which can consider the interrelationship of the attributes. Firstly, score function and accuracy function of intuitionistic linguistic numbers are introduced. Then, an intuitionistic linguistic Bonferroni mean (ILBM) operator and an intuitionistic linguistic weighted Bonferroni mean (ILWBM) operator are developed, and some desirable characteristics of them are studied. At the same time, some special cases with respect to the parameterspandqin Bonferroni are analyzed. Based on the ILWBM operator, the approach to multiple attribute decision making with intuitionistic linguistic information is proposed. Finally, an illustrative example is given to verify the developed approach and to demonstrate its effectiveness.

An Approach to Multiple Attribute Decision Making with Triangular Intuitionistic Fuzzy Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7285-7288
Author(s):  
Jinping Chen
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Construction Projects ◽  
Multiple Attribute Decision Making ◽  
Intuitionistic Fuzzy Sets ◽  
Weighted Averaging ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy ◽  
Operational Laws ◽  
Multiple Attribute

The aim of this paper is to investigate the multiple attribute decision making problems with triangular intuitionistic fuzzy information. Some operational laws of triangular intuitionistic fuzzy sets, score functions of triangular intuitionistic fuzzy sets are introduced. Based on these operational laws, some Einstein aggregation operators, including triangular intuitionistic fuzzy Einstein weighted averaging (TIFEWA) operator, triangular intuitionistic fuzzy Einstein ordered weighted averaging (TIFEOWA) operator and triangular intuitionistic fuzzy Einstein hybrid aggregation (TIFEHA) operator, are proposed. An approach to multiple attribute decision making with triangular intuitionistic fuzzy information is developed based on the TIFEWA operator. Finally, an illustrative example for evaluating the construction projects quality with triangular intuitionistic fuzzy information is given to verify the developed approach.

MODELS FOR MULTIPLE ATTRIBUTE DECISION MAKING WITH INTUITIONISTIC FUZZY INFORMATION

2007 ◽  
Vol 15 (03) ◽  
pp. 285-297 ◽  
Author(s):  
Z. S. XU
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Membership Function ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute

The intuitionistic fuzzy set (IFS) characterized by a membership function and a non-membership function, was introduced by Atanassov [K. Atanassov, "Intuitionistic fuzzy sets", Fuzzy Sets and Systems 20 (1986) 87–96] as a generalization of Zadeh' fuzzy set [L. A. Zadeh, "Fuzzy Sets", Information and Control 8 (1965) 338–353] to deal with fuzziness and uncertainty. In this paper, we investigate the multiple attribute decision making (MADM) problems, in which the information about attribute weights is incomplete, and the attribute values are expressed in intuitionistic fuzzy numbers (IFNs). We first define the concept of intuitionistic fuzzy ideal solution (IFIS), and then, based on the IFIS and the distance measure, we establish some optimization models to derive the attribute weights. Furthermore, based on the developed models, we develop some procedures for the rankings of alternatives under different situations, and extend the developed models and procedures to handle the MADM problems with interval-valued intuitionistic fuzzy information. Finally, we give some illustrative examples to verify the effectiveness and practicability of the developed models and procedures.

SOME CONTINUOUS AGGREGATION OPERATORS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY INFORMATION AND THEIR APPLICATION TO DECISION MAKING

2012 ◽  
Vol 20 (02) ◽  
pp. 185-209 ◽  
Author(s):  
JIAN LIN ◽  
QIANG ZHANG
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Fuzzy Information ◽  
Numerical Examples ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Interval Valued

In this paper, some new operators for aggregating interval-valued intuitionistic fuzzy information are proposed to deal with multiple attribute decision making problems. Firstly, the C-IFOWA operator and C-IFOWG operator are developed to aggregate all the values in the interval-valued intuitionistic fuzzy numbers. Some of their desirable properties are also studied. Secondly, in order to aggregate a set of interval-valued intuitionistic fuzzy numbers, some new aggregation operators are proposed based on the C-IFOWA operator and C-IFOWG operator. Thirdly, two methods for multiple attribute decision making, in which the attribute values are given in the forms of interval-valued intuitionistic fuzzy numbers are presented. Finally, two numerical examples are provided to illustrate the practicality and validity of the proposed methods.

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