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Home›Decision-making›Rough-VIKOR — Rough extension of VIKOR
MCDMRankingrough

Rough-VIKOR — Rough extension of VIKOR

ROUGH-VIKOR (Rough-VIKOR — Rough extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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ROUGH-VIKOR
AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITIC

When to use it

ROUGH-VIKOR (Zhu et al. 2015) extends VIKOR to rough [L,U] intervals. PIS/NIS (f*/f-) are crisp scalars derived from bound extremes — no defuzzification at this step. S and R are rough intervals computed via bound-specific ratio arithmetic (w^L with ratio^L, w^U with ratio^U). Rough Q [L,U] is computed component-wise using crisp extremes S*/S^-/R*/R^-. Final ranking is by Q midpoint (L+U)/2 ascending — lower Q means 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. Zhu, G., Hu, J., Qi, J., Gu, C., Peng, Y. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics DOI: 10.1016/j.aei.2015.01.010 ↗

How to cite this page

ScholarGate. (2026, June 2). Rough-VIKOR — Rough extension of VIKOR. ScholarGate. https://scholargate.app/en/decision-making/rough-vikor

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AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITIC

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Related reference concepts

Decision MakingDecision Support SystemsWeighted ScoresEvaluation CriteriaQuadratic Discriminant AnalysisScoring Rubrics

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

ScholarGate — ROUGH-VIKOR (Rough-VIKOR — Rough extension of VIKOR). Retrieved 2026-07-20 from https://scholargate.app/en/decision-making/rough-vikor · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Zhu, G. Hu, J. Qi, J. Gu, C. Peng, Y.
Subfamily
Ranking
Year
2015
Type
Rough outranking/ranking — Rough number (lower approximation L, upper approximation U)
Value Space
rough
Uncertainty
epistemic
Compensation
full
Rank Reversal
Yes
Related methods
AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITIC
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