Dear Batool
Years ago, and expert and AHP creator, Dr. Tomas Saaty answered that question, asserting that AHP is already fuzzy and then, no further fuzzy treatment was necessary
Dear Batool Alaoui,
Also i suggest you to see links and attched files on topic.
https://core.ac.uk/download/pdf/6580373.pdf
https://core.ac.uk/download/pdf/33278395.pdf
http://isahp.org/2009Proceedings/Final_Papers/50_Meixner_Fuzzy_AHP_REV_FIN.pdf
Article Evaluating the knowledge, relevance and experience of expert...
Article Group Aggregation Techniques for Analytic Hierarchy Process ...
Best regards
Dear Batool,
In FAHP, if there is more than one expert involved in the assessment (i.e. group preference), then their judgments (opinions) can be aggregated using weighted averaging method (e.g. establishing weights for experts based on their years of experience). The total of the weights should add up to 1. Then, you multiply each expert's judgment (fuzzy number) by their weight and finally add all resulting judgments fuzzy numbers together in order to get the aggregate one.
Hope this helps,
Nasser
Dear Nolberto,
You’re right! Tomas Saaty explicitly criticised fuzzifying the AHP method and stated that there is already uncertainty inherent in the nature of the method: i.e. the comparison judgments are already fuzzy because they are allowed to vary over the values of a scale. However, many comparative studies have been made for AHP and FAHP and generally, results indicted that using FAHP leads to better model outcomes than AHP especially when the evaluations made by the decision maker are not much certain.
Nasser
Dear Nasser
Thank you for your words. I like your explanation about the comparative judgements. It clarifies Saaty comments on that subject.
However, I am curious about how these studies predicted better outcomes using FAHP, considering that they don't know the real result
In another words, regarding what yardstick were these comparisons made?
Dare Batool, You can follow same steps used in the Normal AHP with take into consideration the fuzzy arithmetic operations.
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