We formulate a decision model for the risk management of hazardous processes as an optimization problem of a point process. The essential features of the model are: long-term (process lifetime) objective function which is a risk-averse utility function, a dynamic risk model (marked point process model) representing the stochastic process of events observable or unobservable to the decision-maker and a long-term control variable guiding the selection of optimal solutions for short-term problems.
The model is demonstrated by a case study of a hazardous process with reparable safety systems, such as a nuclear power plant. The short-term decision problem of the case study is whether it is sometimes beneficial to temporarily shut the process down in order to cut, off the high risk periods. The long-term decision problem is to optimize a long-term control variable that determines which decision alternative is preferred in a case of increased risk in the process: (1) to shut the process down during the repair time or (2) to continue the operation. Several long-term strategies are analysed and compared. As a solution approach for the optimization problem, we use the stochastic quasi-gradient procedure
