Simulation and uncertainty modeling of project schedules estimates

Project management involves various sources of uncertainty that affect planning, execution schedules, and cost. At the same time, the influx of information can be employed to reduce the uncertainty. This can be efficiently accomplished within the framework of the Bayesian approach. This approach also has the advantage of providing a seamless synthesis of information coming from the field with information generated by data enhancing simulations. We demonstrate the use of this approach in an on-line simulation that augments a real-life monitoring and planning system for managing tunneling construction projects.