Hesitant Bipolar-Valued Intuitionistic Fuzzy set in Multi Attribute Group decision making

2021 ◽  
Vol 8 (5) ◽  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy

scholarly journals The Maximizing Deviation Method Based on Interval-Valued Pythagorean Fuzzy Weighted Aggregating Operator for Multiple Criteria Group Decision Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Liang ◽  
Xiaolu Zhang ◽  
Manfeng Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Pythagorean Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Maximizing Deviation Method ◽  
Interval Valued ◽  
Deviation Method

As a new extension of Pythagorean fuzzy set (also called Atanassov’s intuitionistic fuzzy set of second type), interval-valued Pythagorean fuzzy set which is parallel to Atanassov’s interval-valued intuitionistic fuzzy set has recently been developed to model imprecise and ambiguous information in practical group decision making problems. The aim of this paper is to put forward a novel decision making method for handling multiple criteria group decision making problems within interval-valued Pythagorean fuzzy environment based on interval-valued Pythagorean fuzzy numbers (IVPFNs). There are three key issues being addressed in this approach. The first is to introduce an interval-valued Pythagorean fuzzy weighted arithmetic averaging (IVPF-WAA) operator to aggregate the decision data in order to get the overall preference values of alternatives. Some desirable properties of the IVPF-WAA operator are also investigated. Based on the idea of the maximizing deviation method, the second is to establish an optimization model for determining the weights of criteria for each expert. The third is to construct a minimizing consistency optimal model to derive the weights of criteria for the group. Finally, an illustrating example is given to verify the proposed approach.

scholarly journals Some Complex Intuitionistic Uncertain Linguistic Heronian Mean Operators and Their Application in Multiattribute Group Decision Making

2021 ◽  
Vol 2021 ◽  
pp. 1-31
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Jeonghwan Gwak ◽  
Tahir Mahmood ◽  
Sultan Aljahdali
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Weighted Arithmetic ◽  
Decision Making Problem ◽  
Heronian Mean

In this paper, a new decision-making algorithm has been presented in the context of a complex intuitionistic uncertain linguistic set (CIULS) environment. CIULS integrates the concept the complex of a intuitionistic fuzzy set (CIFS) and uncertain linguistic set (ULS) to deal with uncertain and imprecise information in a more proactive manner. To investigate the interrelation between the pairs of CIULSs, we combine the concept of the Heronian mean (HM) and the complex intuitionistic uncertain linguistic (CIUL) to describe some new operators, namely, CIUL arithmetic HM (CIULAHM), CIUL weighted arithmetic HM (CIULWAHM), CIUL geometric HM (CIULGHM), and CIUL weighted geometric HM (CIULWGHM). The main advantage of these suggested operators is that they considered the interaction between pairs of objects during the formulation process. Also, a number of distinct brief cases and properties of the operators are analyzed. In addition, based on these operators, we have stated a MAGDM (“multiattribute group decision-making”) problem-solving algorithm. The consistency of the algorithm is illustrated by a computational example that compares the effects of the algorithm with a number of well-known existing methods.

An Approach to Command and Control Group Decision-Making Based on Intuitionistic Fuzzy Set

2014 ◽  
Vol 511-512 ◽  
pp. 851-856
Author(s):  
Yan Jie Niu ◽  
Yong Wang ◽  
Dong Ge Zhang ◽  
Zhi Xue Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Command And Control ◽  
Control Group ◽  
Attribute Weight ◽  
Intuitionistic Fuzzy ◽  
And Control

In the process of command and control group decision-making, it is difficult to select appropriate decision schemes due to its attribute weight and evaluation as well as uncertainty of weigh

scholarly journals An Extended TODIM Method for Group Decision Making with the Interval Intuitionistic Fuzzy Sets

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yanwei Li ◽  
Yuqing Shan ◽  
Peide Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Hamming Distance ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute

For a multiple-attribute group decision-making problem with interval intuitionistic fuzzy sets, a method based on extended TODIM is proposed. First, the concepts of interval intuitionistic fuzzy set and its algorithms are defined, and then the entropy method to determine the weights is put forward. Then, based on the Hamming distance and the Euclidean distance of the interval intuitionistic fuzzy set, both of which have been defined, function mapping is given for the attribute. Finally, to solve multiple-attribute group decision-making problems using interval intuitionistic fuzzy sets, a method based on extended TODIM is put forward, and a case that deals with the site selection of airport terminals is given to prove the method.

scholarly journals A GROUP DECISION-MAKING MODEL FOR WASTEWATER TREATMENT PLANS SELECTION BASED ON INTUITIONISTIC FUZZY SETS

2018 ◽  
Vol 26 (4) ◽  
pp. 251-260 ◽  
Author(s):  
Zhexuan Zhou ◽  
Yajie Dou ◽  
Xiaoxiong Zhang ◽  
Danling Zhao ◽  
Yuejin Tan
Keyword(s):  
Decision Making ◽  
Wastewater Treatment ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Treatment Plans ◽  
Decision Making Model

As the need for environmental protection and resource sustainability has increased in recent times, wastewater treatment has become increasingly important. In this paper, a group decision-making model for plans selection in wastewater treatment is proposed. In order to deal with uncertainties and multiple attributes in wastewater treatment, an intuitionistic fuzzy set is employed to evaluate wastewater treatment plans effectively. A distance measure is defined to obtain an objective weight measuring the expert’s judgment. More specifically, experts first use group decision-making on the various plans with an intuitionistic fuzzy set. Meanwhile, Due to the decision-makers psychological behavior, the prospect theory is applied. Next, the various plans are ranked by The Order of Preference by Similarity to Ideal Solution (TOPSIS) method and prospect theory. Finally, an illustrative example of wastewater treatment plans selection is used to verify the proposed model.

GROUP DECISION MAKING METHODOLOGY BASED ON THE ATANASSOV'S INTUITIONISTIC FUZZY SET GENERALIZED OWA OPERATOR

2010 ◽  
Vol 18 (06) ◽  
pp. 801-817 ◽  
Author(s):  
DENG-FENG LI ◽  
LI-LING WANG ◽  
GUO-HONG CHEN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Weighted Averaging ◽  
Owa Operator ◽  
Preference Relations ◽  
Ordered Weighted Averaging ◽  
Intuitionistic Fuzzy

The aim of this paper is to develop a new methodology for solving group decision making problems in which preference comparisons between alternatives are expressed with Atanassov's intuitionistic fuzzy (IF) preference relations. In this methodology, the generalized ordered weighted averaging (GOWA) operator is extended to develop the Atanassov's IF set (IFS) generalized ordered weighted averaging (IFSGOWA) operator, which can aggregate vague or imprecise information expressed with the Atanassov's IFSs. The Atanassov's IFSGOWA operator based methodology is further developed to solve group decision making problems with Atanassov's IF preference relations. A real example of the agroecological region assessment problem is used to illustrate the implementation and applicability of the proposed methodology. It is also shown that the obtained decision results could be affected by the choice of the parameter lambda and the nature of the weights.

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