MULTIMOORA-IFN: A mcdm method based on intuitionistic fuzzy number for performance management

Tomas Baležentis, Shouzhen Zeng, Alvydas Baležentis

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

The paper presents a multi-criteria decision making method to tackle intuitionistic fuzzy numbers, namely MULTIMOORA-IFN. Being an extension of the crisp MULTIMOORA method, the MULTIMOORA-IFN is designed to facilitate group decision making with uncertain information. The proposed methods consists of the three parts—the Ratio System, the Reference Point, and the Full Multiplicative Form—specific with different aggregation techniques. Furthermore, the robustness of the decision making process can be improved by employing ordered aggregation operators, for instance an intuitionistic fuzzy power ordered weighted average operator or an intuitionistic fuzzy power ordered weighted geometric operator. A numerical simulation exhibits the possibilities for application of the proposed method.

Original languageEnglish
JournalEconomic Computation and Economic Cybernetics Studies and Research
Volume48
Issue number4
Publication statusPublished - 2015

Fingerprint

Performance Management
Fuzzy numbers
Decision making
Agglomeration
Aggregation Operators
Group Decision Making
Reference Point
Multicriteria Decision-making
Weighted Average
Operator
Aggregation
Multiplicative
Decision Making
Computer simulation
Robustness
Numerical Simulation
Performance management
MULTIMOORA

Keywords

  • Group decision making
  • IFPOWA
  • Intuitionistic fuzzy number
  • MCDM
  • MULTIMOORA
  • Personnel management

ASJC Scopus subject areas

  • Economics and Econometrics
  • Computer Science Applications
  • Applied Mathematics

Cite this

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AB - The paper presents a multi-criteria decision making method to tackle intuitionistic fuzzy numbers, namely MULTIMOORA-IFN. Being an extension of the crisp MULTIMOORA method, the MULTIMOORA-IFN is designed to facilitate group decision making with uncertain information. The proposed methods consists of the three parts—the Ratio System, the Reference Point, and the Full Multiplicative Form—specific with different aggregation techniques. Furthermore, the robustness of the decision making process can be improved by employing ordered aggregation operators, for instance an intuitionistic fuzzy power ordered weighted average operator or an intuitionistic fuzzy power ordered weighted geometric operator. A numerical simulation exhibits the possibilities for application of the proposed method.

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