## 5 Conclusions  
Based on the maintenance planning problem of fleets driven by mission and reliability, this paper studies the selective maintenance decision-making method considering the health conditions of the fleet and the requirements of missions. Firstly, a selective maintenance model based on virtual age reduction is established according to the problem background, and then a phased problem-solving framework is presented. Finally, a multi-objective optimization algorithm is used to solve the model, and a maintenance strategy solution set satisfying the mission requirements is given. The specific work is summarized as follows:  
1. A selective maintenance decision model of fleets based on virtual age reduction was constructed. In the process of model establishment, the traditional research structure of \"unit-system\" in maintenance planning was extended to the three-level research structure of \"unit-system-fleet\", considering the cooperation of different equipment in missions. Based on the Kijima II imperfect maintenance model, this model uses virtual age to evaluate the health condition of equipment. A cost-based maintenance  
Figure 8: The distribution of the nondominated solution set. evaluation method is proposed considering the service age improvement coefficient, and the mission satisfied capability of a fleet is described by the survival probability. 2. The two-stage problem-solving framework of \"decision-evaluation\" and the corresponding solution method were proposed. The problem is decomposed into two parts: the multiobjective optimization decision of mission satisfied capability and maintenance cost and the strategy evaluation based on maintenance hours considering the convergence rate of the algorithm so as to simplify the difficulty of solving the problem. Based on the sparrow search algorithm, the discrete and multiobjective improvement is made, and the NSGA-II nondominated sorting method and elitist strategy are integrated so that the solution set of nondominated maintenance strategy distributed uniformly in the target space can be quickly obtained. Then, the SA algorithm is used to evaluate the maintenance strategy and give the corresponding optimal maintenance schedule and the minimized maintenance time so as to obtain a series of optimal maintenance strategies that satisfy the mission requirements. 3. In terms of the application of the method, we verified the case of a vehicle fleet, established its selective maintenance decision model and solved it by using the two-stage algorithm proposed in this chapter. A series of selective maintenance schemes of the vehicle fleet uniformly distributed in the target space were obtained, and the effectiveness of the method was verified. The above research methods can be applied to the dynamic selective maintenance decision problem of repairable fleets driven by mission and reliability, optimize maintenance task planning, reduce maintenance cost, improve availability and mission success probability and provide guidance for other similar problems. However, fleets in the real world commonly consist of different types of units. In terms of future directions, a fleet with lager size and different types of vehicles can be take into consideration, which will increase the size of the problem. In addition, future research can focus on the maintenance planning of fleets in multiwave missions and consider the dynamic changes in factors such as task requirements and maintenance resources so as to achieve the optimal performance of the fleet in the overall task. Conceptualization, Q.C. and X.Y. ; methodology, Q.C., P.W. and X.Y. ; software, P.W. and L.Y. ; validation Q.C. and P.W. ; formal analysis, L.Y. and J.W. ; investigation P.W., L.Y. and J.W. ; resources Q.C. and L.Y. ; data curation L.Y. and J.W. ; writing--original draft preparation, P.W. and L.Y. ; writing--review and editing, Q.C. and J.W. ; project administration, Q.C. and X.Y. All authors have read and agreed to the published version of the manuscript. This research received no external funding.