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Home›Decision-making›Mixed Aggregation by Comprehensive Normalization Technique
MCDMRankingcrisp

Mixed Aggregation by Comprehensive Normalization Technique

MACONT (Mixed Aggregation by Comprehensive Normalization Technique) is a ranking multi-criteria decision-making (MCDM) method introduced by Wen, Z. Liao, H. Zavadskas, E. K. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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When to use it

MACONT mitigates normalization sensitivity by averaging across multiple normalization approaches.

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. Wen, Z., Liao, H., Zavadskas, E. K. (2020). MACONT: Mixed Aggregation by Comprehensive Normalization Technique for Multi-Criteria Analysis. Informatica 31(4):857-880 DOI: 10.15388/20-INFOR417 ↗

How to cite this page

ScholarGate. (2026, June 2). Mixed Aggregation by Comprehensive Normalization Technique. ScholarGate. https://scholargate.app/en/decision-making/macont

Similar methods

DNMAHF-VIKORWASPASWEDBAROUGH-MABACLOGARITHMIC-NORMALIZATIONZ-VIKORZ-BWM

Related reference concepts

Decision Support SystemsDecision MakingWeighted ScoresCriteria for Decision-Making under Risk and UncertaintyEvaluation CriteriaEconometric Modeling

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

ScholarGate — MACONT (Mixed Aggregation by Comprehensive Normalization Technique). Retrieved 2026-07-20 from https://scholargate.app/en/decision-making/macont · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Wen, Z. Liao, H. Zavadskas, E. K.
Subfamily
Ranking
Year
2020
Type
Hybrid aggregation combining multiple normalization methods to reduce bias
Value Space
crisp
Uncertainty
None
Compensation
partial
Rank Reversal
No
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