m-Polar Hesitant Fuzzy extension of TOPSIS
MHF-TOPSIS (m-Polar Hesitant Fuzzy extension of TOPSIS) is a ranking multi-criteria decision-making (MCDM) method introduced by Akram, M., Adeel, A., Alcantud, J.C.R. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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
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How it works
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When to use it
MHF-TOPSIS (Akram et al. 2019) extends classical TOPSIS to m-Polar Hesitant Fuzzy multi-criteria group decision-making (MCGDM). Each cell of the decision matrix is an m-tuple of HFEs, one per pole/sub-feature of the criterion; the m poles are independent (no DHF-style γ⁺+η⁺ constraint). The DM-chosen prolongation_mode (optimistic = repeat max, pessimistic = repeat min) equalises pole-HFE lengths to a common r. Weighting is literal scalar multiplication (H′ = w·H). Ideals mHP_IS and mHN_IS are pole-wise column extrema on the weighted matrix; distances average over q criteria × m poles × r posit
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.
Common pitfalls
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Sources
- 1.Akram, M., Adeel, A., Alcantud, J.C.R. (2019). Multi-Criteria Group Decision-Making Using an m-Polar Hesitant Fuzzy TOPSIS Approach. Symmetry
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Cite this page
ScholarGate. (2026, June 2). MHF-TOPSIS. ScholarGate. https://scholargate.app/decision-making/mhf-topsis