Analysis of Scheduling Uncertainty in Stochastic Resource Constrained Networks

Uncertainties in project scheduling are recognized as significant obstacles to complete projects on schedule. Previous research on stochastic resource constrained project scheduling problems mainly focused on developing some scheduling policies to minimize the expected project duration, yet, the work on addressing and quantifying schedule uncertainty is rare in these approaches. The objective of this report is to propose an approach to measure the scheduling uncertainty in terms of schedule entropy, in the problem environment. A two-stage approach is proposed in this paper. By the approach, the evolution of the stochastic resource constrained projects can be simplified into the reduced scenario tree based on a decision criterion, a risk measure expected utility and entropy, which can reflects to project manager's attitude to risk. On the basis of the reduced scenario tree, the scheduling uncertainty of projects are investigated and measured as well as the minimal expected project duration can be obtained from the tree. Finally, a simple example is demonstrated.