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Home›Decision-making›Simplified PROBID using Top/Bottom Quartile Ideal Sets
MCDMRankingcrisp

Simplified PROBID using Top/Bottom Quartile Ideal Sets

SPROBID (Simplified PROBID using Top/Bottom Quartile Ideal Sets) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, Z., Rangaiah, G. P., Wang, X. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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SPROBID
AHPBWMCRITICENTROPY

When to use it

Higher p_i = better. SPROBID is faster than PROBID: uses top/bottom ⌊m/4⌋ ideals instead of half. Best for m ≥ 4. For m < 4 falls back to trivial case.

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
  • Assumes full compensation — a strong score on one criterion can offset a weak score on another.

Sources

  1. Wang, Z., Rangaiah, G. P., Wang, X. (2021). Preference ranking on the basis of ideal-average distance method for multi-criteria decision-making. Industrial & Engineering Chemistry Research DOI: 10.1021/acs.iecr.1c01413 ↗

How to cite this page

ScholarGate. (2026, June 2). Simplified PROBID using Top/Bottom Quartile Ideal Sets. ScholarGate. https://scholargate.app/en/decision-making/sprobid

Related methods

AHPBWMCRITICENTROPY

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Similar methods

PROBIDROUGH-TOPSISROUGH-VIKORQR-TOPSISSPOTISDHF-TOPSISQR-VIKORROUGH-MABAC

Related reference concepts

Decision Support SystemsDecision MakingEvaluation CriteriaDecision Making SkillsWeighted ScoresComputer Software Selection

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

ScholarGate — SPROBID (Simplified PROBID using Top/Bottom Quartile Ideal Sets). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/sprobid · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Wang, Z., Rangaiah, G. P., Wang, X.
Subfamily
Ranking
Year
2021
Type
Multi-ideal distance ranking with quartile-based ideal selection
Value Space
crisp
Uncertainty
None
Compensation
full
Rank Reversal
No
Related methods
AHPBWMCRITICENTROPY
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