Stochastic gradient-based time-cost tradeoffs in PERT networks using simulation

Infinitesimal perturbation analysis and score function gradient estimators are developed for PERT (Program Evaluation and Review Technique) networks and analyzed for potential use for prescriptive project management. In particular, a stochastic version of the familiar deterministic ‘project crashing’ problem is considered. A heuristic using the gradient estimators is developed and shown to give close to locally optimal performance relatively quickly. An attempt is made to characterize the amount of variability in networks that would warrant the use of this heuristic by comparing its performance experimentally to that of the standard linear programming approach using only the task means (ignoring variability).