An application of investment decision with random fuzzy outcomes

In this study, an investment problem associated with purchasing machine is solved by using decision trees method. The main difference of this paper from the others in the decision tree literature is using random fuzzy variables, which includes randomness and fuzziness simultaneously, for modeling demand quantities and demand state probabilities. Demand quantities and demand state probabilities are modeled as a continuous and discrete random fuzzy variables, respectively. The random fuzzy variables are transformed to fuzzy variables and crisp numbers by using the properties of the random fuzzy variable, fuzzy variable and normal distribution. After the transformation, the chance and decision nodes removals processes are performed to solve the problem.