Multiple criteria decision analysis using correlation-based precedence indices within pythagorean fuzzy uncertain environments

Jih Chang Wang, Ting Yu Chen*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

11 Scopus citations

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.

Original languageEnglish
Pages (from-to)911-924
Number of pages14
JournalInternational Journal of Computational Intelligence Systems
Volume11
Issue number1
DOIs
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018, the Authors.

Keywords

  • Assignment model
  • Comprehensive discordance index
  • Correlation-based precedence index
  • Discordance indicator
  • Multiple criteria decision analysis
  • Pythagorean fuzzy set

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