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Home›Decision-making›Intuitionistic Fuzzy Entropy Weight Method (Vlachos-Sergiadis 2007 entropy measure as applied by Hung-Chen 2010)
MCDMWeight Objectiveintuitionistic

Intuitionistic Fuzzy Entropy Weight Method (Vlachos-Sergiadis 2007 entropy measure as applied by Hung-Chen 2010)

IF-ENTROPY (Intuitionistic Fuzzy Entropy Weight Method (Vlachos-Sergiadis 2007 entropy measure as applied by Hung-Chen 2010)) is a weight objective multi-criteria decision-making (MCDM) method introduced by Atanassov, K. T. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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IF-ENTROPY
IF-ARASIF-COCOSOIF-CODASIF-COPRASIF-EDASIF-GRAIF-MABACIF-MARCOSIF-PROMETHEEIF-TODIM

+6 more

When to use it

IF-ENTROPY is an OBJECTIVE weighting method (Family = Weight_Objective): the criterion weights are derived from the information content of the decision matrix itself, not elicited from the DM. Use IF-ENTROPY when the DM cannot or does not wish to provide subjective criterion preferences. The output is a crisp weight vector on the n-simplex, which can then feed any IF ranking method (IF-TOPSIS, IF-MAUT, IF-VIKOR, etc.). The IF entropy formula (Vlachos-Sergiadis 2007) is symmetric under criterion-direction complement, so cost vs benefit criteria do not need pre-processing. Multi-DM aggregation v

Strengths & limitations

Strengths
  • Follows a transparent, reproducible computational procedure that can be audited step by step.
  • Handles multiple criteria of differing scales and units within a single decision matrix.
Limitations
  • Assumes full compensation — a strong score on one criterion can offset a weak score on another.

Sources

  1. Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems DOI: 10.1016/S0165-0114(86)80034-3 ↗

How to cite this page

ScholarGate. (2026, June 2). Intuitionistic Fuzzy Entropy Weight Method (Vlachos-Sergiadis 2007 entropy measure as applied by Hung-Chen 2010). ScholarGate. https://scholargate.app/en/decision-making/if-entropy

Related methods

IF-ARASIF-COCOSOIF-CODASIF-COPRASIF-EDASIF-GRAIF-MABACIF-MARCOS

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

  • IF-ARASDecision-making↔ compare
  • IF-COCOSODecision-making↔ compare
  • IF-CODASDecision-making↔ compare
  • IF-COPRASDecision-making↔ compare
  • IF-EDASDecision-making↔ compare
  • IF-GRADecision-making↔ compare
  • IF-MABACDecision-making↔ compare
  • IF-MARCOSDecision-making↔ compare
Compare side by side →

Referenced by

IF-ARASIF-EDASIF-PROMETHEEIF-TODIMIF-TOPSISIVIF-ARASIVIF-MABACIVIF-TODIMIVIF-VIKORTIFN-CODAS

Similar methods

IF-PROMETHEEIF-MAUTIF-TODIMIF-TOPSISIF-VIKORIF-WASPASIF-GRAIF-MULTIMOORA

Related reference concepts

Decision MakingDecision Support SystemsWeighted ScoresDecision Making SkillsDelphi TechniqueK-Means Clustering

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — IF-ENTROPY (Intuitionistic Fuzzy Entropy Weight Method (Vlachos-Sergiadis 2007 entropy measure as applied by Hung-Chen 2010)). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/if-entropy · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Atanassov, K. T.
Subfamily
Weight Objective
Year
1986
Type
Information-theoretic objective weighting under Intuitionistic Fuzzy uncertainty (IF entropy → divergence → simplex-normalised crisp weights)
Value Space
intuitionistic
Uncertainty
epistemic
Compensation
full
Rank Reversal
No
Related methods
IF-ARASIF-COCOSOIF-CODASIF-COPRASIF-EDASIF-GRAIF-MABACIF-MARCOS
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