scholarly journals An Approach to Evaluate the Clothing Creative Design with Dual Hesitant Fuzzy Information

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Ya-Mei Li
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Creative Design ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Decision Making Problem

The problem of evaluating the clothing creative design with dual hesitant fuzzy information is the multiple attribute decision making problem. In this paper, we have utilized dual hesitant fuzzy hybrid average (DHFHA) operator to develop the model to solve the multiple attribute decision making problems for evaluating the clothing creative design. Finally, a practical example for evaluating the clothing creative design is given to verify the developed approach.

scholarly journals Multiple-Attribute Decision-Making Problem Using TOPSIS and Choquet Integral with Hesitant Fuzzy Number Information

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Harish Garg ◽  
Abazar Keikha ◽  
Hassan Mishmast Nehi
Keyword(s):  
Decision Making ◽  
Fuzzy Number ◽  
Choquet Integral ◽  
Multiple Attribute Decision Making ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Collection Data ◽  
Topsis Technique

The paper aims are to present a method to solve the multiple-attribute decision-making (MADM) problems under the hesitant fuzzy set environment. In MADM problems, the information collection, aggregation, and the measure phases are crucial to direct the problem. However, to handle the uncertainties in the collection data, a hesitant fuzzy number is one of the most prominent ways to express uncertain and vague information in terms of different discrete numbers rather than a single crisp number. Additionally, to aggregate and to rank the collective numbers, a TOPSIS (“Technique for Order of Preference by Similarity to Ideal Solution”) and the Choquet integral (CI) are the useful tools. Keeping all these features, in the present paper, we combine the TOPSIS and CI methods for hesitant fuzzy information and hence present a method named as TOPSIS-CI to address the MADM problems. The presented method has been described with a numerical example. Finally, the validity of the stated method as well as a comparative analysis with the existing methods is addressed in detail.

scholarly journals Linguistic Picture Fuzzy Dombi Aggregation Operators and Their Application in Multiple Attribute Group Decision Making Problem

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 764 ◽  
Author(s):  
Muhammad Qiyas ◽  
Saleem Abdullah ◽  
Shahzaib Ashraf ◽  
Lazim Abdullah
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Comparison Analysis ◽  
Fuzzy Information ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Operational Rule ◽  
Picture Fuzzy Sets

The aims of this study are to propose the linguistic picture fuzzy Dombi (LPFD) aggregation operators and decision-making approach to deal with uncertainties in the form of linguistic picture fuzzy sets. LPFD operators have more flexibility due to the general fuzzy set. Utilizing the Dombi operational rule, the series of Dombi aggregation operators were proposed, namely linguistic picture fuzzy Dombi arithmetic/geometric, ordered arithmetic/ordered geometric and Hybrid arithmetic/Hybrid geometric aggregation operators. The distinguished feature of these proposed operators is studied. At that point, we have used these Dombi operators to design a model to deal with multiple attribute decision-making (MADM) issues under linguistic picture fuzzy information. Finally, an illustrative example to evaluate the emerging technology enterprises is provided to demonstrate the effectiveness of the proposed approach, together with a sensitivity analysis and comparison analysis, proving that its results are feasible and credible.

TOPSIS Method for Multiple Attribute Decision Making Problem in Intuitionistic Fuzzy Setting

2013 ◽  
Vol 427-429 ◽  
pp. 1888-1891
Author(s):  
Yuan Yuan He ◽  
Zai Wu Gong
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Topsis Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Setting

This paper is concerned with a TOPSIS method for fuzzy multiple attribute decision making, in which the information about attribute weights is completely known and the attribute values take form of intuitionistic fuzzy numbers. A class of distance for describing the deviation degrees between intuitionistic fuzzy sets is used to measure difference between two alternatives. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees. Then, we apply the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their closeness coefficients. Finally, a numerical example is given to show the feasibility and effectiveness of the method.

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.

scholarly journals A Method Based on Intuitionistic Fuzzy Dependent Aggregation Operators for Supplier Selection

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Fen Wang ◽  
Shouzhen Zeng ◽  
Chonghui Zhang
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Intuitionistic Fuzzy ◽  
Strategic Factor ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Decision Making Problem

Recently, resolving the decision making problem of evaluation and ranking the potential suppliers have become as a key strategic factor for business firms. In this paper, two new intuitionistic fuzzy aggregation operators are developed: dependent intuitionistic fuzzy ordered weighed averaging (DIFOWA) operator and dependent intuitionistic fuzzy hybrid weighed aggregation (DIFHWA) operator. Some of their main properties are studied. A method based on the DIFHWA operator for intuitionistic fuzzy multiple attribute decision making is presented. Finally, an illustrative example concerning supplier selection is given.

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.

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