A genetic algorithm solution for a nuclear power plant risk–cost maintenance model

Reliability Centered Maintenance (RCM) is one of the popular maintenance optimization methods according to certain kinds of priorities. Traditional RCM usually analyzes and optimizes the maintenance strategy from the viewpoint of component instead of the whole maintenance program impact. Research presented in this paper is a pilot study using PSA techniques in RCM. How to reflect the effect on component unavailability by the maintenance activities such as surveillance testing and preventive maintenance in PSA model is discussed firstly. Based on the discussion, a maintenance risk–cost model is established for global maintenance optimization in a nuclear power plant, and a genetic algorithm (GA) is applied to solve such a model to get the global optimized maintenance strategy. Finally, the result got from a simple test case based on a risk–cost model consisting of 10 components is presented.