ScholarGate
Get started
MCDMDecision-makingRankingMath steps

Neutrosophic MABAC

OriginatorPeng, Xindong Dai, JingguoYear2018Sources1

N-MABAC (Neutrosophic MABAC) is a ranking multi-criteria decision-making (MCDM) method introduced by Peng, Xindong Dai, Jingguo in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

Key highlights

  • 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.

Intuition

This section is available to Pro members. Upgrade to Pro

How it works

This section is available to Pro members. Upgrade to Pro

When to use it

Use N-MABAC when expert assessments involve truth (T), indeterminacy (I), and falsity (F) components.

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.

Common pitfalls

This section is available to Pro members. Upgrade to Pro

Sources

  1. 1.
    Peng, Xindong, Dai, Jingguo (2018). Approaches to single-valued neutrosophic MADM based on MABAC, TOPSIS and new similarity measure with score function. Neural Computing and Applications
    DOI 10.1007/s00521-016-2607-y

You have read it. What now?

Ask about this method

Cite this page

ScholarGate. (2026, June 2). N-MABAC. ScholarGate. https://scholargate.app/decision-making/n-mabac

Neutrosophic MABAC | ScholarGate