For a PERT network, a new method is developed for estimating the criticality index of activity i (ACIi) as a function of the expected duration of activity i (μi) and for the sensitivity analysis of the expected project completion time (μT) with respect to μi. The proposed method evaluates the frequency of activity i being on the critical path, and thereby its ACIi, using Monte Carlo simulation or a Taguchi orthogonal array experiment at several values of μi, fits a logistic regression model for estimating ACIi as a function of μi, and then, using the estimated ACIi function, evaluates the amount of change in μT when μi is changed by a given amount. Unlike the previous works, the proposed method models ACIi as a nonlinear (i.e., logistic) function of μi, which can be used to estimate the amount of change in μT for a variety of changes in μi. Computational results indicate that the performance of the proposed method is comparable to that of direct Monte Carlo simulation.
