Joint selective maintenance and mission abort decisions for mission-critical systems

This paper presents a novel model to jointly optimize selective maintenance scheduling and mission abort decisions for mission-critical systems. The proposed model applies to various critical systems whose reliability configuration is a three-block structure where the main block is in series with a two-block cold standby unit. Given limited maintenance resources, only a subset of the system components undergo maintenance during intermission breaks to achieve the subsequent missions with a predetermined minimum performance. During a mission, if the active/online block in the standby unit fails before reaching a predefined mission abort decision threshold, the mission is aborted, and a rescue operation is initiated, relying on the reserve block of the standby unit. However, if failure occurs after the threshold, the mission proceeds as planned. To address this joint optimization problem, a mixed-integer nonlinear programming model is formulated to minimize expected total maintenance, mission failure, and penalty costs. A genetic algorithm is developed to solve this optimization model effectively. Extensive experiments validate the proposed model and highlight the benefits of jointly optimizing mission abort decisions and maintenance planning. Results indicate that including a mission abort decision threshold achieves a reasonable mission success probability and enhances system survivability compared to the case without an abort policy.