Supplier Quality Evaluation Using a Fuzzy Multi Criteria Decision Making Approach - Complex System Modelling and Control Through Intelligent Soft Computations - page 202

observing the effects on the decision. This is useful in situations where uncertainties
exist in the de nition of the importance of different factors. In our case, we will

conduct sensitivity analysis to see the importance of criteria weights in evaluating
supplier quality.

3.4 Results Validation

To validate the model results, we will compare the results of our study with another
standard approach called Fuzzy Simple Aggregated Weighting (SAW). This
method is de ned as follows.

3.4.1 Fuzzy SAW

Let w j represent the weight of the criteria j and x ij represents the rating of alternative
i against criteria j.

Step 1: Normalize the data using the following equations.

x ij
max
i

r ij ¼

8 ¼ ; ; ...; ; ¼ ; ; ...; ð Þ ð 15 Þ

i 1 2 m j 1 2 n benefit type criteria

f x ij g

min
i

x ij g
x ij

f

r ij ¼ 8 i ¼ 1 ; 2 ; ...; m ; j ¼ 1 ; 2 ; ...; n ð cost type criteria Þ ð 16 Þ

Step 2: Calculate the overall performance rating ui i for alternative i by aggre-
gating the product of its various criteria values with their respective
weights.

X

u i ¼ w j x ij ð 17 Þ

j

Step 3: Select the alternative with the highest overall performance value

u i 8 i ¼ 1 ; 2 ; ... m