Academy
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Ranking
PIV - Proximity Indexed Value
Distance from weighted ideal minimization via linear proximity index
Mufazzal, S., Muzakkir, S. M.2018doi:10.1016/j.cie.2018.03.045 ↗
Overview
PIV uses absolute differences from ideal (not squared); more resistant to rank reversal than TOPSIS.
- Output
- numeric score
- Data
- Crisp
- Weights
- Needs a weight source
Edge cases and pitfalls
Mix of benefit/cost directions without separate normalization
How to cite
Mufazzal, S.; Muzakkir, S. M. (2018). A new multi-criterion decision making (MCDM) method based on proximity indexed value for minimizing rank reversals. Computers & Industrial Engineering. https://doi.org/10.1016/j.cie.2018.03.045
System ID, as it appears in reports and the API
PIV