Random variate generation for discrete fuzzy numbers based on α-cuts

Probabilistic based random variate generation is the most popular method for representing randomness into simulation scenarios that could occur in real life. The main idea behind the use of random numbers to replicate the value of a uncertain variable can also be extended to fuzzy sets, including discrete fuzzy sets. This way, it is possible to use random numbers and the α -cut of a discrete fuzzy set to retrieve a random variate alongside its membership degree. To do so, a method for computing discrete fuzzy random variates based on α -cuts is proposed and applied to two examples: a comprehensive and a simulation example.