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Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets

Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets Recently, a new model based on Pythagorean fuzzy set (PFS) has been presented to manage the uncertainty in real‐world decision‐making problems. PFS has much stronger ability than intuitionistic fuzzy set to model such uncertainty. In this paper, we define some novel operational laws of PFSs and discuss their desirable properties. For the multicriteria decision‐making problems with PFSs, we propose an extended technique for order preference by similarity to ideal solution method to deal effectively with them. In this approach, we first propose a score function based comparison method to identify the Pythagorean fuzzy positive ideal solution and the Pythagorean fuzzy negative ideal solution. Then, we define a distance measure to calculate the distances between each alternative and the Pythagorean fuzzy positive ideal solution as well as the Pythagorean fuzzy negative ideal solution, respectively. Afterward, a revised closeness is introduced to identify the optimal alternative. At length, a practical example is given to illustrate the developed method and to make a comparative analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Systems Wiley

Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets

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References (44)

Publisher
Wiley
Copyright
Copyright © 2014 Wiley Periodicals, Inc.
ISSN
0884-8173
eISSN
1098-111X
DOI
10.1002/int.21676
Publisher site
See Article on Publisher Site

Abstract

Recently, a new model based on Pythagorean fuzzy set (PFS) has been presented to manage the uncertainty in real‐world decision‐making problems. PFS has much stronger ability than intuitionistic fuzzy set to model such uncertainty. In this paper, we define some novel operational laws of PFSs and discuss their desirable properties. For the multicriteria decision‐making problems with PFSs, we propose an extended technique for order preference by similarity to ideal solution method to deal effectively with them. In this approach, we first propose a score function based comparison method to identify the Pythagorean fuzzy positive ideal solution and the Pythagorean fuzzy negative ideal solution. Then, we define a distance measure to calculate the distances between each alternative and the Pythagorean fuzzy positive ideal solution as well as the Pythagorean fuzzy negative ideal solution, respectively. Afterward, a revised closeness is introduced to identify the optimal alternative. At length, a practical example is given to illustrate the developed method and to make a comparative analysis.

Journal

International Journal of Intelligent SystemsWiley

Published: Jan 1, 2014

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