MCDMDecision-makingRankingMath steps

m-Polar Fuzzy Linguistic TOPSIS for MCGDM (Adeel, Akram & Koam 2019, Symmetry 11(6):735) — multi-criteria group decision-making via m-polar fuzzy linguistic variables (mFLV), expert-aggregated m-PF linguistic decision matrix, aggregated linguistic-term-set weights, m-PF linguistic positive/negative ideal solutions (mPIS / mNIS), m-PF linguistic Euclidean distances, relative closeness coefficient E'_j descending ranking

OriginatorAdeel, A., Akram, M., Koam, A. N. A.Year2019Sources1Related methods8

MPF-TOPSIS-LING (m-Polar Fuzzy Linguistic TOPSIS for MCGDM (Adeel, Akram & Koam 2019, Symmetry 11(6):735) — multi-criteria group decision-making via m-polar fuzzy linguistic variables (mFLV), expert-aggregated m-PF linguistic decision matrix, aggregated linguistic-term-set weights, m-PF linguistic positive/negative ideal solutions (mPIS / mNIS), m-PF linguistic Euclidean distances, relative closeness coefficient E'_j descending ranking) is a ranking multi-criteria decision-making (MCDM) method introduced by Adeel, A., Akram, M., Koam, A. N. A. in 2019. It turns a decision matrix of alternative

Key highlights

  • 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.

Intuition

This section is available to Pro members. Upgrade to Pro

How it works

This section is available to Pro members. Upgrade to Pro

When to use it

Read the result as a complete descending ranking of alternatives a_j by the relative m-PF linguistic closeness coefficient E'_j = D_e(a_j, mNIS) / (D_e(a_j, mPIS) + D_e(a_j, mNIS)) ∈ [0,1]. A value close to 1 means the alternative is simultaneously close to the m-PF linguistic positive ideal solution mPIS and far from the m-PF linguistic negative ideal solution mNIS, so higher E'_j is strictly better. The mPIS / mNIS are computed per-column per-pole over the weighted aggregated matrix E, so they always sit on the boundary of the alternative set and depend on which alternatives are present — re

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
  • 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.

Common pitfalls

This section is available to Pro members. Upgrade to Pro

Sources

  1. 1.
    Adeel, A., Akram, M., Koam, A. N. A. (2019). Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method. Symmetry (MDPI)

You have read it. What now?

Cite this page

ScholarGate. (2026, June 2). MPF-TOPSIS-LING. ScholarGate. https://scholargate.app/decision-making/mpf-topsis-ling

MPF-TOPSIS-LING | ScholarGate