Application of a Multi-Objective Optimization to Risk-Based Inservice Testing Available to Purchase

This paper proposes a methodology to apply a multi-objective optimization to risk-based inservice testing with robustness. The multi-objective optimization is applied to solve the trade-off between maintenance costs and unavailability of a standby system and then assist in determining the robust solution. In order to obtain the most robust solution, the decision-making method for the multi-objective optimization in the viewpoint of robustness is proposed. The risk ranking and revising risk-ranking processes are then used to assist in finding the most optimal surveillance test interval based on risk management. The applicability of the proposed methodology is confirmed by case studies for a standby system of a simplified high-pressure injection system (HPIS) in a nuclear power plant’s pressurized water reactor (PWR). The results showed that the proposed methodology provides the effective scheme to achieve the most optimal surveillance test interval based on risk and robustness.