Polynomial Function and Fuzzy Inference for Evaluating the Project Performance under Uncertainty

The objectives of this paper are two folds. The first one is to improve the time forecasting produced from the well known Earned Value Management (EVM), using the polynomial function. The time prediction observed from the polynomial model, which is compared against that observed from the most common method for time forecasting (critical path method), is a more accurate (mean absolute percentage of error is less than 2%) than that observed from the conventional deterministic forecasting methods (CDFMs). The second is to evaluate and forecast the overall project performance under uncertainty using the fuzzy inference. As the uncertainty is inherent in real life projects, the polynomial function and fuzzy inference model (PFFI) can assist the project managers, to estimate the future status of the project in a more robust and reliable way. Two examples are used to illustrate how the new method can be implemented in reality. Keywords-Cost Control; Earned Value; Fuzzy; Forecasting; Polynomial; Probabilistic.