User Guide

• 1. MCDM methods
  • 1.1. American school
    • 1.1.1. ARAS
    • 1.1.2. AROMAN
    • 1.1.3. COCOSO
    • 1.1.4. CODAS
    • 1.1.5. COPRAS
    • 1.1.6. EDAS
    • 1.1.7. ERVD
    • 1.1.8. LoPM
    • 1.1.9. MABAC
    • 1.1.10. MAIRCA
    • 1.1.11. MARCOS
    • 1.1.12. MOORA
    • 1.1.13. OCRA
    • 1.1.14. PROBID
    • 1.1.15. RAM
    • 1.1.16. RAFSI
    • 1.1.17. RIM
    • 1.1.18. SPOTIS
    • 1.1.19. TOPSIS
    • 1.1.20. VIKOR
    • 1.1.21. WASPAS
    • 1.1.22. WPM
    • 1.1.23. WSM
  • 1.2. European school
    • 1.2.1. PROMETHEE II
  • 1.3. Rule based
    • 1.3.1. COMET
  • 1.4. Other MCDM Methods
    • 1.4.1. LoPM Method
    • 1.4.2. LMAW Method
• 2. Weighting methods
  • 2.1. Objective weights
    • 2.1.1. Equal weights
    • 2.1.2. Entropy method
    • 2.1.3. Standard deviation method
    • 2.1.4. MEREC
    • 2.1.5. CRITIC method
    • 2.1.6. CILOS method
    • 2.1.7. IDOCRIW method
    • 2.1.8. Angular method
    • 2.1.9. Gini Coeficient method
    • 2.1.10. Statistical variance method
    • 2.1.11. LOPCOW method
  • 2.2. Subjective weights
    • 2.2.1. AHP
    • 2.2.2. RANCOM
• 3. Normalizations methods
  • 3.1. Sum based
    • 3.1.1. Sum normalization
    • 3.1.2. Vector normalization
    • 3.1.3. Logarithmic normalization
    • 3.1.4. Enhanced accuracy method
  • 3.2. Linear ratio based
    • 3.2.1. Max normalization
    • 3.2.2. Linear normalization
    • 3.2.3. Nonlinear normalization
  • 3.3. Linear max-min based
    • 3.3.1. Min-max normalization
    • 3.3.2. Zavadskas and Turkis normalization
• 4. Correlation module
  • 4.1. Spearman correlation coefficient
  • 4.2. Weighted Spearman correlation coefficient
  • 4.3. Kendall rank correlation coefficient
  • 4.4. Ranking similarity coefficient
  • 4.5. Pearson’s correlation coefficient
  • 4.6. Goodman-Kruskal correlation coefficient
  • 4.7. Weighted Similarity Coefficient
• 5. Distance module
  • 5.1. draWS Distance
  • 5.2. Kemeny Distance
  • 5.3. Frobenius Distance Between Rankings