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Home›Decision-making›Logarithm Methodology of Additive Weights
MCDMRankingcrisp

Logarithm Methodology of Additive Weights

LMAW (Logarithm Methodology of Additive Weights) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Žižović, M., Biswas, S., Božanić, D. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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  1. MCDM
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  3. 1 Sources
  4. PUBLISHED
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LMAW
AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITICF-LMAW

When to use it

Q_i ∈ [0, n] where n = number of criteria. Higher Q means better alternative. Q_i is the sum over criteria of the sigmoid-weighted ξ_ij ∈ (0, 2). Direction is handled in F1 via Pamucar 2021 Eq.(2): benefit standardisation (x+max)/max, cost standardisation (x+min)/x — both produce ϑ_ij > 1 with best alternative receiving largest ϑ. F1 → F2 (log-norm) → F3 (sigmoid weighting) → F4 (sum) is the canonical pipeline.

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. Pamučar, D., Žižović, M., Biswas, S., Božanić, D. (2021). A new logarithm methodology of additive weights (LMAW) for multi-criteria decision-making: Application in logistics. Facta Universitatis, Series: Mechanical Engineering DOI: 10.22190/FUME210214031P ↗

How to cite this page

ScholarGate. (2026, June 2). Logarithm Methodology of Additive Weights. ScholarGate. https://scholargate.app/en/decision-making/lmaw

Related methods

AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITIC

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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Referenced by

F-LMAW

Similar methods

F-LMAWZF-LMAWLBWALOPCOWLOGARITHMIC-NORMALIZATIONFUZZY-SIWECRAWECSIWEC

Related reference concepts

Decision MakingDecision Support SystemsWeighted ScoresLogistic DiscriminationCriteria for Decision-Making under Risk and UncertaintyLogistic Regression

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

ScholarGate — LMAW (Logarithm Methodology of Additive Weights). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/lmaw · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Pamučar, D., Žižović, M., Biswas, S., Božanić, D.
Subfamily
Ranking
Year
2021
Type
Logarithm-based additive weighting
Value Space
crisp
Uncertainty
None
Compensation
full
Rank Reversal
No
Related methods
AHPANPBWMBWM-BAYESIANCCSDCILOSCIMASCRITIC
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