Abstract
Mission abort decisions require balancing mission success against system survival, often under economic constraints that necessitate profit-driven policies. Distinct from previous profit-driven models that either neglect external shocks or are limited to single-component systems, this paper develops a profit driven abort and inspection policy for multi-component systems subject to random shocks. Each component undergoes deterioration and potential failure under an independent shock process. At inspection, both the component state and the cumulative number of shocks are observed, enabling the evaluation of task success and rescue completion probabilities for surviving components using a proposed probabilistic modeling method. These assessments inform an optimal selection of components to continue or abort as well as the inspection time, such that the expected profit of mission (EPM) is maximized. The proposed model is demonstrated and validated through case studies involving a swarm of five unmanned aerial vehicles (UAVs) that carry out a payload delivery mission from different source locations along distinct routes to a common destination. Both homogeneous and heterogeneous UAV configurations are considered. Sensitivity analyses are performed to examine the impacts of mission success reward, mission demand requirement, component capacity, and shock rate on the optimal inspection timing and the corresponding EPM, offering managerial insights into profit-driven abort decision-making.