Multiple Criteria Decision Analysis Using Correlation-Based Precedence Indices Within Pythagorean Fuzzy Uncertain Environments
- DOI
- 10.2991/ijcis.11.1.69How to use a DOI?
- Keywords
- Pythagorean fuzzy set; correlation-based precedence index; multiple criteria decision analysis; discordance indicator; comprehensive discordance index; assignment model
- Abstract
The theory of Pythagorean fuzzy sets possesses significant advantages in handling vagueness and complex uncertainty. Additionally, Pythagorean fuzzy information is useful to simulate the ambiguous nature of subjective judgments and measure the fuzziness and imprecision more flexibly. The aim of this research is to develop an effective assignment-based method using a novel concept of correlation-based precedence indices for conducting multiple criteria decision analysis within the Pythagorean fuzzy uncertain environment. Based on the ideas of information energy and correlations, this paper defines a novel concept of correlation-based precedence indices in the Pythagorean fuzzy context and discusses their desirable properties. Next, this paper presents some useful concepts of discordance indicators, weighted discordance indicators, comprehensive discordance indicators, and comprehensive discordance indices to construct a novel assignment model for acquiring a comprehensive ranking of candidate alternatives. As an application of the proposed assignment-based method, a practical example concerning a financing decision of working capital policies is provided to demonstrate its practicality and effectiveness.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Jih-Chang Wang AU - Ting-Yu Chen PY - 2018 DA - 2018/04/09 TI - Multiple Criteria Decision Analysis Using Correlation-Based Precedence Indices Within Pythagorean Fuzzy Uncertain Environments JO - International Journal of Computational Intelligence Systems SP - 911 EP - 924 VL - 11 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.11.1.69 DO - 10.2991/ijcis.11.1.69 ID - Wang2018 ER -