This study uses a p-timed Petri net to represent the initial scheduling of a project: places are tasks and each place has assigned a initial cost and a initial time execution. Risk management is applied to project scheduling in order to identify and mitigate risks where uncertain variables are modelled as stochastic variables. The algorithm determines the set of mitigation actions that reduce the risk exposure stated in the chance constraints of the proposed optimization problem. This work shows how this problem can be modelled as a stochastic optimization problem requiring that constraints should be held with a probability exceeding /spl alpha/.
['Ascension Zafra-Cabeza', 'Miguel A. Ridao', 'Eduardo F. Camacho']
Chance constrained project scheduling under risk