An accurate estimation of future cash flows is a crux for decision makers during the selection of economic alternatives. Often, such estimations are imprecise because decision makers do not posses enough knowledge about the future events that may affect the cash flows. Usually, such estimations are secured either by pure human intuition, statistical methodologies (e.g., regression analysis), or combinations of these. Regardless of the data source, the risk of an alternative is measured by the dispersion (i.e., variance) of the cash flow estimations (Fabrycky et al. 1998). The measure of this risk is possible because cash flows estimations are often assumed to be normally distributed and rely on the Central Limit Theorem (Taha 1997). This paper presents an approach of how to deal with the imprecision of future cash flows that do not rely on the above theorem. The approach deals with the selection of economic alternatives when cash flows are modeled as triangular fuzzy numbers and the internal rate of return is used as the criterion decision. Although the example presented in this paper considered a symmetric imprecision (or vagueness) about the most promising value of the cash flows, a more realistic situation can be easily modeled by using asymmetry on the cash flows.

This paper illustrates an application that does not rely on the central limit theorem to deal with the imprecision of estimated cash flows.