System-of-Systems Resilient Recovery Time Estimation via Heterogeneous Capacity Distribution

This paper focuses on optimization-based resilient recovery time estimation for system-of-systems (SoS) with diverse resources and capacities. Regarding the crew dispatch in a large-scale SoS, it’s natural to see distinct crews possess different capacities and performance in the reparation of alternative physical component systems (PCSs). Facing with inevitable malfunctions of PCSs, the proposed optimization strategy incorporates not only the crew dispatch and PCS restoration, but also the heterogeneous capacity distribution that reflects the cooperation inside the SoS. The designed multi-objective optimization function minimizes the crew travel time, malfunction lost and potential risk. The estimation of recovery time is calculated based on the solution to the optimization. The case study is performed on a large-scale SoS with 9 inoperable PCSs, 8 crews and 8 types of faults with alternative repair times, which shows the effectiveness of the proposed strategy.