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The proposed approach herein quantifies uncertainty based on possibility theory.
Possibility theory finally allows a graded evaluation of expected performances.
Possibility theory (Dubois & Prade 1988) is based on fuzzy set theory (Zadeh 1978).
The seemingly small differences between possibility theory and ranking theory thus turn out to be crucial.
As shown by the example in Section 3.2, this is not the case for possibility theory.
Probability theory and possibility theory are the two main methods to describe the measurement uncertainty.
The basic building block in the possibility theory is named possibility distribution.
Subsequently, possibility theory was developed by many researchers such as Dubois and Prade [22, 23].
These methods are still developing and often use fuzzy sets, possibility theory and belief functions.
We construct a solution algorithm based on bi-level programming and possibility theory.
Since then the possibility theory has been studied by many researchers.
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