| In this work titled 'Stochastic Project Scheduling System: Implications for Risk Management' we develop a stochastic risk model for the project's network depicted by more general Stochastic Petri Nets. The model expresses the uncertainty about activities' duration, and it includes contingency plans and repetition cycles. Uncertainty about the successful or failed outcome of the project as a whole or of its activities is characterized probabilistically.; The random variables bound to activity durations are modelled by probability distributions. After a Monte Carlo simulation, scheduling and multiresource allocation algorithms are executed in order to collect aggregated measures that depict a comprehensive information about the expected behaviour of the stochastic project network.; The feasibility of our proposal has been proven by a software prototype built in JavaRTM. The program reads a project or a multiproject as input, executes the scheduling algorithms, and displays information such as criticality, success chance, resource consumption, cost, makespan, etc.; The risk model and the prototype have been tested in a set of small-sized projects chosen from the literature and from the professional practise. The experiments have shown that the information we get for project risk management is more extensive and precise than the one you could get with previous techniques.; This risk model could be very significant in some new areas managed by projects such as research, information technology or aggressive product development, where the risk factor is high. |
