k/N系统维修时机与备件携行量联合优化

针对任务期间舰载k/N系统的维修保障问题，以出航准备阶段维修与携行备件的配置为背景展开研究。结合k/N系统的使用及维修过程，以部件可修为前提建立了维修与携行备件的联合优化模型。模型以装备使用可用度为约束条件，以保障费用最低为目标函数，决策变量包括维修启动条件、备件携行量和维修人员数量3个参数。采用边际分析法对模型进行求解，分析了传统算法存在的问题，并提出了对应的改进措施。算例包括3部分：一是用仿真对比验证了所建模型，结果表明本文模型具有较小的误差；二是以枚举法得出的最优解为基准，对传统算法与改进后算法的性能进行了比较，结果表明改进后的算法可明显减小与枚举法最优解的相对误差，提高寻优概率；三是对各项改进措施的贡献做了相应测试。

Joint optimization of maintenance time and carrying spare parts for k-out-of-N system

Maintenance support of repairable warship k-out-of-N system during a task was researched. A method of how to trade off maintenance frequency, carrying spare parts and repair capacity was given. Taking the three parameters as decision variables and combined with the using and maintenance processes of k-out-of-N system, a joint optimization model of maintenance and carrying spare parts was established, in which operational availability was taken as a constraint condition and minimal maintenance costs as objective function, and repair initial condition, numbers of carrying spare parts and numbers of repair men were taken as decision variables. A modified marginal analysis algorithm was applied to solve the model through improving some drawbacks of the traditional one, and the drawbacks and corresponding improvements were also listed. Three tests were done: firstly, in order to verify the proposed model, a simulation for k-out-of-N system was implemented, and the results show that the absolute error of the proposed model is very small; second, using the optimal solution of enumeration as benchmark, performances of traditional marginal analysis algorithm and its modified algorithm were compared, and the results show that the modified algorithm has lower error and can enhance optimizing probability; third, the contribution of each modified item to marginal analysis algorithm was respectively tested.