Method and Applications for Multiple Attribute Decision-Making Based on Converting Triangular Fuzzy Numbers into Connection Numbers

2017 ◽  
pp. 281-292 ◽  
Author(s):  
Qing Shen ◽  
Yunliang Jiang ◽  
Xiongtao Zhang ◽  
Jing Fan ◽  
Yong Liu
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Triangular Fuzzy Numbers ◽  
Multiple Attribute

A Method to Extend TOPSIS for Fuzzy Multiple Attribute Decision Making

2013 ◽  
Vol 634-638 ◽  
pp. 3936-3939
Author(s):  
Yuan Yuan He ◽  
Zai Wu Gong
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Triangular Fuzzy Numbers ◽  
Fuzzy Information ◽  
Topsis Method ◽  
Fuzzy Distance ◽  
Relative Closeness ◽  
Multiple Attribute ◽  
Two Alternatives

The TOPSIS method is developed for solving the problem of fuzzy multiple attribute decision making, in which the attribute values take the form of triangular fuzzy numbers. A new distance for triangular fuzzy numbers is introduced to measure difference between two alternatives. And we apply the similarity degree derived from the new fuzzy distance to design a model of TOPSIS. Then, we utilize the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their relative closeness. Finally, an illustrative example is given to demonstrate the proposed approach practicality and effectiveness.

scholarly journals Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators

Mathematics ◽  
2018 ◽  
Vol 6 (11) ◽  
pp. 236 ◽  
Author(s):  
Xiumei Deng ◽  
Jie Wang ◽  
Guiwu Wei ◽  
Mao Lu
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Special Kind ◽  
Multiple Attribute Decision Making ◽  
Linguistic Terms ◽  
Multiple Integration ◽  
Multiple Attribute ◽  
Pythagorean Fuzzy Numbers ◽  
Actual Decision

The Hamy mean (HM) operator, as a useful aggregation tool, can capture the correlation between multiple integration parameters, and the 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs) are a special kind of Pythagorean fuzzy numbers (PFNs), which can easily describe the fuzziness in actual decision making by 2-tuple linguistic terms (2TLTs). In this paper, to consider both Hamy mean (HM) operator and 2TLPFNs, we combine the HM operator, weighted HM (WHM) operator, dual HM (DHM) operator, and dual WHM (DWHM) operator with 2TLPFNs to propose the 2-tuple linguistic Pythagorean fuzzy HM (2TLPFHM) operator, 2-tuple linguistic Pythagorean fuzzy WHM (2TLPFWHM) operator, 2-tuple linguistic Pythagorean fuzzy DHM (2TLPFDHM) operator and 2-tuple linguistic Pythagorean fuzzy DWHM (2TLPFDWHM) operator. Then some multiple attribute decision making (MADM) procedures are developed based on these operators. At last, an applicable example for green supplier selection is given.

scholarly journals DENSITY AGGREGATION OPERATORS BASED ON THE INTUITIONISTIC TRAPEZOIDAL FUZZY NUMBERS FOR MULTIPLE ATTRIBUTE DECISION MAKING

2014 ◽  
Vol 19 (Supplement_1) ◽  
pp. S454-S470 ◽  
Author(s):  
Peide Liu ◽  
Xiaocun Yu
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Expected Value ◽  
Aggregation Operators ◽  
Ranking Method ◽  
Interval Numbers ◽  
Trapezoidal Fuzzy Numbers ◽  
Multiple Attribute

With respect to the multiple attribute decision making problems in which the attribute values take the form of the intuitionistic trapezoidal fuzzy numbers, some methods based on density aggregation operators are proposed. Firstly, the definition, expected value and the ranking method of intuitionistic trapezoidal fuzzy numbers are introduced, and the method of calculating density weighted vector is proposed. Then some density aggregation operators based on interval numbers and intuitionistic trapezoidal fuzzy numbers are developed, and a multiple attribute decision making method is presented. Finally an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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