PERT (Program Evaluation and Review Technique), developed in the 1950’s, represented the first attempt to udincorporate uncertainty in project scheduling. Despite some weaknesses, it is still widely used in project udmanagement mostly thanks to the simplicity of its algorithm in operating on activity network diagrams. Today the udincreasing complexity of projects requires new techniques and the increasing availability of computer power have udnot brought project simulation into common usage as expected. Although several reviews assert that simulative udapproach has already superseded PERT when coping with uncertain environment; the reason why it is not diffused udis that simulations require a too long computing time. In this paper we show through an algorithm and experimental udresults that the computational time, historically the major drawback of Monte Carlo simulations, is definitely udminimum thanks also to the computational power available nowadays. We present results of an efficient program udmade of few lines of code and able to compute the completion time of a network activity diagram with 100.000 udactivities and about 50.000.000 precedence constraints between them.
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