scholarly journals TOPSIS Method Based on Correlation Coefficient and Entropy Measure for Linguistic Pythagorean Fuzzy Sets and Its Application to Multiple Attribute Decision Making

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Mingwei Lin ◽  
Chao Huang ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Fuzzy Topsis ◽  
Multiple Attribute Decision Making ◽  
Entropy Measure ◽  
Security Evaluation ◽  
Topsis Method ◽  
Pythagorean Fuzzy Set ◽  
Multiple Attribute ◽  
Topsis Technique

The linguistic Pythagorean fuzzy set (LPFS) is an important implement for modeling the uncertain and imprecise information. In this paper, a novel TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed for LPFSs based on correlation coefficient and entropy measure. To this end, the correlation coefficient is proposed for the relationship measurement between LPFSs. Afterwards, two entropy measures are developed to calculate the attribute weight information. Then, a novel linguistic Pythagorean fuzzy TOPSIS (LPF-TOPSIS) method is proposed to solve multiple attribute decision-making problems. Finally, the LPF-TOPSIS method is applied to handle a case concerning the selection of firewall productions, and then, a case concerning the security evaluation of computer systems is given to conduct the comparative analysis between the proposed LPF-TOPSIS method and previous decision-making methods for validating the superiority of the proposed LPF-TOPSIS method.

scholarly journals EVALUATION OF ALTERNATIVES APPLYING TOPSIS METHOD IN A FUZZY ENVIRONMENT

2005 ◽  
Vol 11 (4) ◽  
pp. 242-247 ◽  
Author(s):  
Jurgita Antuchevičiene
Keyword(s):  
Real Life ◽  
Fuzzy Topsis ◽  
Multiple Attribute Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Fuzzy Environment ◽  
Attribute Analysis ◽  
Relative Closeness ◽  
Multiple Attribute ◽  
Topsis Technique

The paper analyses the problem of multiple attribute decision‐making (MADM) under fuzzy environment. In some cases the crisp value is inadequate to model real‐life situations. For this reason some fuzzy MADM methods have been developed. The extended TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) to fuzzy environment is presented in the current paper. Weights and ratings of each criterion are described in triangular fuzzy numbers. The relative closeness to the ideal solution of each alternative is calculated applying different approaches that were presented in different scientific papers. A computational experiment is presented to compare the results of a multiple attribute analysis that uses three modifications of fuzzy TOPSIS method in a particular situation.

scholarly journals Sistem Pendukung Keputusan Pemberian Reward Pegawai Menggunakan Metode TOPSIS

2020 ◽  
Vol 18 (1) ◽  
pp. 11
Author(s):  
Aisyah Mutia Dawis
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Selection Process ◽  
Multiple Attribute Decision Making ◽  
Management Problem ◽  
Multiple Attribute ◽  
Ideal Solutions ◽  
Order Preference ◽  
Topsis Technique ◽  
A Company

Every company has management providing wages or rewards to employees. This is because employees are one of the resources that are used as a driving force in advancing a company. Besides, many companies provide rewards to their employees with the aim of motivating employees to help more. There is management problem in PKU Muhammadiyah Gamping Hospital for determining the number of rewards obtained by employees because many variables are determined. Therefore, the need of management information system can facilitate the Management of the PKU Muhammadiyah Gamping Hospital in determining decision making for providing rewards. One method that is often used in implementing decision support systems is Multiple Attribute Decision Making (MADM), focusing TOPSIS (Technique for Order Preference with Similarities to Ideal Solutions). By the implementation of the decision support system, PKU Muhammadiyah Gamping Hospital can carry out the selection process more efficiently.The test results by matching the employee data results at PKU Muhammadiyah Hospital obtained 95.83% accuracy so that this system can help the PKU Muhammadiyah Hospital in determining employee rewards.

Schemes Selection of Yarn Tension Detection and Control Based on Fuzzy Multiple Attribute Group Decision Making

2013 ◽  
Vol 694-697 ◽  
pp. 2829-2834
Author(s):  
Yan Li ◽  
Hui Min Li ◽  
Yi Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Yarn Tension ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
The Individual ◽  
Topsis Technique ◽  
And Control

To evaluate the yarn tension detection and control schemes in rapier looms, a fuzzy multiple-attribute group decision making problem is proposed for the schemes selection. Firstly, important degrees of every attributes from each expert are considered. The individual opinions of each expert are integrated with the similarity of the decision group. And the synthesized weights of each expert are calculated. Secondly, with the aggregation of experts opinions, the group attribute-weights matrixes are obtained. Then the fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is used to sequence the alternatives, and the optimal scheme is decided for yarn tension detection and control system, the decision results illustrate the feasibility and effectiveness of the developed method.

Improved Correlation Coefficients of Quadripartitioned Single-Valued Neutrosophic Sets and Interval-Quadripartitioned Neutrosophic Sets

2020 ◽  
pp. 331-363
Author(s):  
Mohanasundari M. ◽  
Mohana K.
Keyword(s):  
Decision Making ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Multiple Attribute Decision Making ◽  
Neutrosophic Sets ◽  
Statistical Measures ◽  
Multiple Attribute

A correlation coefficient is one of the statistical measures that helps to find the degree of changes to the value of one variable predict change to the value of another. Quadripartitioned single valued neutrosophic sets is an improvization of Wang's single valued neutrosophic sets. This chapter deals the improved correlation coefficients of quadripartitioned single valued neutrosophic sets, interval quadripartitioned neutrosophic sets, and investigates its properties. And this concept is also applied in multiple-attribute decision-making methods with quadripartitioned single valued neutrosophic environment and interval quadripartitioned neutrosophic environment. Finally an illustrated example is given in the proposed method to the multiple-attribute decision-making problems.

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