Fuzzy Entropic Ordered Weighted Averaging Operator and Its Application in Group Decision Making

In this paper, triangular cubic hesitant fuzzy Einstein weighted averaging (TCHFEWA) operator, triangular cubic hesitant fuzzy Einstein ordered weighted averaging (TCHFEOWA) operator and triangular cubic hesitant fuzzy Einstein hybrid weighted averaging (TCHFEHWA) operator are proposed. An approach to multiple attribute group decision making with linguistic information is developed based on the TCHFEWA and the TCHFEHWA operators. Furthermore, we establish various properties of these operators and derive the relationship between the proposed operators and the existing aggregation operators. Finally, a numerical example is provided to demonstrate the application of the established approach.

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INTUITIONISTIC FUZZY GENERALIZED PROBABILISTIC ORDERED WEIGHTED AVERAGING OPERATOR AND ITS APPLICATION TO GROUP DECISION MAKING

Technological and Economic Development of Economy ◽

10.3846/20294913.2014.984253 ◽

2015 ◽

Vol 22 (2) ◽

pp. 177-193 ◽

Cited By ~ 35

Author(s):

Shouzhen ZENG ◽

Weihua SU ◽

Chonghui ZHANG

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Weighted Averaging ◽

Uncertain Environments ◽

Intuitionistic Fuzzy Numbers ◽

Ordered Weighted Averaging ◽

Intuitionistic Fuzzy ◽

Wide Range ◽

Ordered Weighted Averaging Operator

In this paper, we present the intuitionistic fuzzy generalized probabilistic ordered weighted averaging (IFGPOWA) operator. It is a new aggregation operator that uses generalized means in a unified model between the probability and the OWA operator. The main advantage of this new operator is that it is able to deal with probabilities (objective information) and ordered weighted averages (subjective information) in the same formulation. Moreover, it is also able to deal with uncertain environments that can be assessed with intuitionistic fuzzy numbers. Furthermore, it uses generalized means providing a very general formulation that includes a wide range of situations. We study some of its main properties and particular cases such as the generalized intuitionistic fuzzy ordered weighted averaging (GIFOWA) operator and intuitionistic fuzzy probabilistic ordered weighted averaging (IFPOWA) operator. We end the paper by applying the new operator to a group decision making problem concerning the selection of investments.

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Some Generalized Single Valued Neutrosophic Linguistic Operators and Their Application to Multiple Attribute Group Decision Making

Journal of Systems Science and Information ◽

10.21078/jssi-2017-148-15 ◽

2017 ◽

Vol 5 (2) ◽

pp. 148-162 ◽

Cited By ~ 2

Author(s):

Ruipu Tan ◽

Wende Zhang ◽

Shengqun Chen

Keyword(s):

Decision Making ◽

Similarity Measure ◽

Group Decision Making ◽

Group Decision ◽

Weighted Averaging ◽

Attribute Weights ◽

Ordered Weighted Averaging ◽

Aggregate Information ◽

Multiple Attribute

Abstract This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are obtained by using the entropy of neutrosophic linguistic sets. Then three generalized single valued neutrosophic linguistic operators are introduced, including the generalized single valued neutrosophic linguistic weighted averaging (GSVNLWA) operator, the generalized single valued neutrosophic linguistic ordered weighted averaging (GSVNLOWA) operator and the generalized single valued neutrosophic linguistic hybrid averaging (GSVNLHA) operator, and the GSVNLWA and GSVNLHA operators are used to aggregate information. Furthermore, similarity measure based on single valued neutrosophic linguistic numbers is defined and used to sort the alternatives and obtain the best alternative. Finally, an illustrative example is given to demonstrate the feasibility and effectiveness of the developed method.

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Fuzzy Linguistic Induced Ordered Weighted Averaging Operator and Its Application

Journal of Applied Mathematics ◽

10.1155/2012/210392 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 9

Author(s):

Sidong Xian

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Weighted Averaging ◽

Attribute Weights ◽

Operational Laws ◽

Multiple Attribute ◽

Ordered Weighted Averaging Operator ◽

Fuzzy Linguistic ◽

Magdm Problems

With respect to multiple attribute group decision making (MAGDM) problems, in which the attribute weights take the form of real numbers, and the attribute values take the form of fuzzy linguistic scale variables, a decision analysis approach is proposed. In this paper, we develop a new fuzzy linguistic induce OWA (FLIOWA) operator and analyze the properties of it by utilizing some operational laws of fuzzy linguistic scale variables. A method based on the FLIOWA operators for multiple attribute group decision making is presented. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

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ON GROUP DECISION MAKING UNDER LINGUISTIC ASSESSMENTS

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488599000258 ◽

1999 ◽

Vol 07 (04) ◽

pp. 301-308 ◽

Cited By ~ 3

Author(s):

CONG CUONG BUI

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Group Decision Making ◽

Decision Model ◽

Group Decision ◽

Weighted Averaging ◽

Ordered Weighted Averaging ◽

Choice Processes ◽

Aggregation Processes ◽

The Individual

In this paper we consider a fuzzy logic-based model in group decision making, with a focus on the set of all alternatives and on the individual lingustic preference relations. Some choice processes are devoted to the model using consensus measures and linguistic ordered weighted averaging (LOWA) operator. A multiple criteria group decision model in linguistic setting and some aggregation processes are also considered. The model and the new processes allow to incorporate human consistency in decision support systems.

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SOME ICOWA OPERATORS AND THEIR APPLICATIONS TO GROUP DECISION MAKING WITH INTERVAL FUZZY PREFERENCE RELATIONS

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488513500281 ◽

2013 ◽

Vol 21 (04) ◽

pp. 579-601 ◽

Cited By ~ 2

Author(s):

LIGANG ZHOU ◽

ZHIFU TAO ◽

HUAYOU CHEN ◽

JINPEI LIU

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Optimization Model ◽

Group Decision ◽

Weighted Averaging ◽

Preference Relations ◽

Ordered Weighted Averaging ◽

Cowa Operator ◽

Fuzzy Preference Relations ◽

Fuzzy Preference

We develop some new cases of the induced continuous ordered weighted averaging (ICOWA) operator and study their desirable properties, which are very suitable to deal with group decision making (GDM) with interval fuzzy preference relations. First, we present the consensus indicator ICOWA (CI-ICOWA) operator which uses the consensus indicator of the interval fuzzy preference as the order inducing variable in the ICOWA operator. Then the concept of compatibility degree (CD) for two interval fuzzy preference relations is defined based on the continuous ordered weighted averaging (COWA) operator and the compatibility degree ICOWA (CD-ICOWA) operator is proposed which uses the CD as the order inducing variable in the ICOWA operator. Next, we investigate some desirable properties of the CD-ICOWA operator. Additionally, we construct an optimization model to obtain the weights of experts by minimizing the compatibility degree in the GDM. Finally, an illustrative numerical example is used to verify the developed approaches.

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