International Journal of Intelligent Systems· 2014Q1
Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets
- 1,487citations
- Q1SCImago
- 2014year
Short summary
A new Pythagorean Fuzzy Set (PFS) based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is developed to handle multi-criteria decision-making problems with uncertainty.
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Key points
- Introduces new operational laws and properties for Pythagorean Fuzzy Sets (PFSs).
- Proposes an extended TOPSIS method specifically for multi-criteria decision-making with PFSs.
- Develops a score function to determine Pythagorean fuzzy positive and negative ideal solutions.
- Defines a distance measure and a revised closeness coefficient for ranking alternatives.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. International Journal of Intelligent Systems, 2014 · DOI ↗
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Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences