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Home›Decision-making›Fuzzy Decision by Opinion Score Method
MCDMRankingcrisp

Fuzzy Decision by Opinion Score Method

FDOSM (Fuzzy Decision by Opinion Score Method) is a ranking multi-criteria decision-making (MCDM) method introduced by Mohammed, K. I. Zaidan, A. A. Zaidan, B. B. Albahri, O. S. Albahri, A. S. Alsalem, M. 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

FDOSM is well-suited for group decision making with qualitative criteria. Fuzzy aggregation reduces individual bias.

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
  • Results depend on the chosen normalisation, weights, and parameter settings.

Sources

  1. Mohammed, K. I., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Albahri, A. S., Alsalem, M. A. (2019). Real-time remote health-monitoring systems in a medical centre: a review of the provision of healthcare services-based body sensor information, open challenges and methodological aspects. Journal of Medical Systems link ↗

How to cite this page

ScholarGate. (2026, June 2). Fuzzy Decision by Opinion Score Method. ScholarGate. https://scholargate.app/en/decision-making/fdosm

Similar methods

FUZZY-TODIMFUZZY-VIKORQR-TODIMDHF-TODIMQR-MOORAFUZZY-DELPHIFUZZY-MULTIMOORAFUCOM-F

Related reference concepts

Decision Support SystemsDecision MakingWeighted ScoresDecision Making SkillsEvaluation CriteriaParticipative Decision Making

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

ScholarGate — FDOSM (Fuzzy Decision by Opinion Score Method). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/fdosm · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Mohammed, K. I. Zaidan, A. A. Zaidan, B. B. Albahri, O. S. Albahri, A. S. Alsalem, M. A.
Subfamily
Ranking
Year
2019
Type
Linguistic multi-DM opinion aggregation using fuzzy set scoring
Value Space
crisp
Uncertainty
None
Compensation
partial
Rank Reversal
No
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