Fuzzy TOPSIS (Chen-Hwang 1992) — Trapezoidal fuzzy TOPSIS with Zadeh sup-min similarity distance
FUZZY-TOPSIS (Fuzzy TOPSIS (Chen-Hwang 1992) — Trapezoidal fuzzy TOPSIS with Zadeh sup-min similarity distance) is a ranking multi-criteria decision-making (MCDM) method introduced by Chen, S.-J., Hwang, C.-L. in 1992. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Read the full method
Sign in with a free account to read this section.
Method map
The neighbourhood of related methods — select a node to explore.
When to use it
C_i in [0, 1]. Higher C_i means the alternative is closer to the fuzzy PIS A* and farther from the fuzzy NIS A^- under Zadeh's max-min similarity. Rank by descending C_i. Chen-Hwang 1992 trapezoidal arithmetic with linear scale transformation normalisation and Chen-Hwang generalized mean ranking for PIS/NIS extraction.
Strengths & limitations
- 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.
- May exhibit rank reversal when alternatives are added to or removed from the set.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Sources
- Chen, S.-J., Hwang, C.-L. (1992). Fuzzy Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 375, Springer-Verlag, Berlin DOI: 10.1007/978-3-642-46768-4 ↗
How to cite this page
ScholarGate. (2026, June 2). Fuzzy TOPSIS (Chen-Hwang 1992) — Trapezoidal fuzzy TOPSIS with Zadeh sup-min similarity distance. ScholarGate. https://scholargate.app/en/decision-making/fuzzy-topsis
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.
Compare side by side →