Can someone explain why (if at all) it would be a bad idea to use fuzzy numbers in order to represent uncertainties in model parameters instead of probability distributions?
To motivate my question - assume a decision model where the parameters are provided as probability distributions. The information to support the decision is computed by performing a Monte Carlo simulation that evaluates the model for each sample drawn from the parameter distributions and gives the result in terms of the computed sampled probability distribution. From the resulting pd, one can compute the expected value, risk, and other statistical measures.
Could one simply use fuzzy numbers in place of pds and apply fuzzy arithmetic instead of MC?