Abstract
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 (ie, 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.
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Acknowledgements
We thank two anonymous referees for their valuable comments and suggestions that improved the original manuscript. We are also grateful to The Institute for Operations Research and the Management Sciences for permission to use in Kleindorfer (1971).