Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers

1 Equal importance 1 1 1
2 Equal to moderate importance 1 2 3
3 Moderate importance 2 3 4
4 Moderate to strong importance 3 4 5
5 Strong importance 4 5 6
6 Strong to very strong importance 5 6 7
7 Very strong importance 6 7 8
8 Very strong to Extreme importance 7 8 9
9 Extreme importance 8 9 10

 

Fuzzy AHP approach to passenger aircraft type selection

1 Just equal 1 1 1
2 Equally important 0.5 1 1.5
3 Weakly important 1 1.5 2
4 Strongly important 1.5 2 2.5
5 Very strongly important 2 2.5 3
6 Extremely preferred 2.5 3 3.5

 

 Fuzzy AHP as a tool for prioritization of key performance indicators

 

1 Equally important 1 1 1
2 intermediate value between 1 and 3 1 2 3
3 Slightly important 2 3 4
4 intermediate value between 3 and 5 3 4 5
5 Important 4 5 6
6 intermediate value between 5 and 7 5 6 7
7 Strongly important 6 7 8
8 intermediate value between 7and 9 7 8 9
9 Extremely important 9 9 9

Estimating probability of success of escape, evacuation, and rescue (EER) on the offshore platform by integrating Bayesian Network and Fuzzy AHP  

1 Equally important 1` 1 1
2 Weakly more important 1 3/2 2
3 Moderately more important 3/2 2 5/2
4 Strongly more important 2 5/2 3
5 Extremely more important 5/2 3 7/2

Modeling the critical success factors of women entrepreneurship using Fuzzy AHP Framework

1 Equally 1 1 1
2 Very lower 1 2 3
3 Lower 2 3 4
4 Medium 3 4 5
5 Higher 4 5 6
6 Very higher 5 6 7
7 Excellent 7 8 9

Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies

1 Equally importance 0 1 1
2 Weak importance of one over another 1 3 5
3 Strong importance 3 5 7
4 Very strong importance 5 7 9
5 Absolute importance 9 9 10

Using Fuzzy AHP to manage Intellectual Capital assets: An application to the ICT service industry

1 JUST EQUAL 1 1 1
2 EQUALLY important 0.667 1 1.5
3 WEAKLY MORE important 1 1.5 2
4 MODERATERLY MORE important 1.5 2 2.5
5 STRONGLY MORE important 2 2.5 3
6 EXTREMELY MORE important 2.5 3 3.5

A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection

1 Of little importance 0 0 0.25
2 Moderately important 0 0.25 0.5
3 Important 0.25 0.5 0.75
4 Very important 0.5 0.75 1
5 Absolutely important 0.75 1 1

Prioritising solutions for Lean Six Sigma adoption barriers through fuzzy AHP-modified TOPSIS framework

1 Equally Importance/preference 1 1 3
2 Weak importance/preference 1 3 5
3 Strong Importance/preference 3 5 7
4 Very strong importance/preference 5 7 9
5 Extremely strong importance/preference 7 9 11

Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods

1 Equal 1 1 1
2 Weak 0.5 1 1.5
3 Fairly strong 1.5 2 2.5
4 Very strong 2.5 3 3.5
5 Absolute 3.5 4 4.5