Evaluating project completion time in Project Networks with Discrete Random Activity Durations

Deterministic models for project scheduling suffer from the fact that they assume complete information and neglect random influences, that occur during project execution. A typical consequence is the underestimation of the project duration as frequently observed in practice. This phenomenon occurs even in the absence of resource constraints and has been the subject of extensive research in the scientific community. This paper presents a method for obtaining relevant information about the project makespan for scheduling models, with dependent random processing time available in the form of scenarios.