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Home›Decision-making›Hesitant Fuzzy Weighted Aggregated Sum Product Assessment
MCDMRankinghesitant

Hesitant Fuzzy Weighted Aggregated Sum Product Assessment

HF-WASPAS (Hesitant Fuzzy Weighted Aggregated Sum Product Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Mishra, A.R., Rani, P., Pardasani, K.R., Mardani, A. in 2019. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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When to use it

HF-WASPAS ranks alternatives based on performance scores. Higher score = better rank.

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.

Sources

  1. Mishra, A.R., Rani, P., Pardasani, K.R., Mardani, A. (2019). A novel hesitant fuzzy WASPAS method for assessment of green supplier problem based on exponential information measures. Journal of Cleaner Production DOI: 10.1016/j.jclepro.2019.117901 ↗

How to cite this page

ScholarGate. (2026, June 2). Hesitant Fuzzy Weighted Aggregated Sum Product Assessment. ScholarGate. https://scholargate.app/en/decision-making/hf-waspas

Similar methods

HF-COPRASHF-ARASDHF-COPRASHF-MABACQR-WASPASPF-WASPASBF-WASPASHF-EDAS

Related reference concepts

Decision Support SystemsDecision MakingWeighted ScoresCriteria for Decision-Making under Risk and UncertaintyDecision Making SkillsParticipative Decision Making

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

ScholarGate — HF-WASPAS (Hesitant Fuzzy Weighted Aggregated Sum Product Assessment). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/hf-waspas · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Mishra, A.R., Rani, P., Pardasani, K.R., Mardani, A.
Subfamily
Ranking
Year
2019
Type
Hesitant fuzzy WSM+WPM hybrid ranking
Value Space
hesitant
Uncertainty
epistemic
Compensation
full
Rank Reversal
Yes
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