Expected losses minimization in missions with multi-phase rescue procedure

Existing mission aborting models assume that a single-phase rescue procedure (RP) is activated and executed upon the termination of the primary mission to save the asset. In some real-world applications, multiple phases of RP may be engaged. During different RP phases, the system may operate with different performance under different random environments modeled by different shocks arrival processes. This paper pioneers the modeling of such multi-phase RP in the mission aborting systems, where the primary mission and different RP phases may be subject to different aborting policies. A probabilistic approach is put forward for evaluating the mission success probability (MSP) and system survival probability (SSP) of the considered system under any given phase aborting policies, based on which the expected mission losses (EML) is further derived. An optimization problem is then formulated and solved, which finds the optimal aborting policies of all phases, minimizing the EML. An unmanned aerial vehicle (UAV) payload delivery mission system is analyzed to demonstrate the multi-phase RP and the proposed methodology. Impacts of different RP phase sequences, mission failure penalty, payload cost and shock rates on the MSP, SSP, and EML and on the optimal solutions are also investigated through the UAV case study.