Multiple Criteria Group Decision Making Using a Parametric Linear Programming Technique for Multidimensional Analysis of Preference Under Uncertainty of Pythagorean Fuzziness

This paper aims to utilize the core structure of linear programming technique for multidimensional analysis of preference (LINMAP) to propose a parametric LINMAP methodology for addressing multiple criteria group decision-making problems based on Pythagorean fuzzy sets. To compare Pythagorean member...

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Bibliographic Details
Published in:IEEE access Vol. 7; pp. 174108 - 174128
Main Author: Chen, Ting-Yu
Format: Journal Article
Language:English
Published: Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
closeness-based order relation
Decision analysis
Decision making
Entropy
Fuzzy sets
Goodness of fit
Indexes
Linear programming
Multiple criteria group decision making
Multiple criterion
Pythagorean fuzzy set
Pythagorean membership grade
Rail transportation
Uncertainty
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:This paper aims to utilize the core structure of linear programming technique for multidimensional analysis of preference (LINMAP) to propose a parametric LINMAP methodology for addressing multiple criteria group decision-making problems based on Pythagorean fuzzy sets. To compare Pythagorean membership grades, this paper presents a Hamming distance-based approach for identifying closeness-based order relations based on Pythagorean fuzzy closeness indices. The concept of comprehensive closeness measures is introduced to measure individual order consistency and inconsistency between subjective preference relations and objective order relations. In the spirit of LINMAP, this paper determines individual goodness of fit and poorness of fit and further constructs a novel parametric LINMAP model. The applicability of the developed approach is explored by a practical application of railway project investment. Some comparative analyses are conducted to demonstrate the usefulness and advantages of the proposed methodology.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2957161