多指标约束下备件可修复库存方案优化

针对在机场集团运行期间,设备备件可修复的多指标约束问题,提出了基于近似可用度评估的可修备件库存优化方法。首先分析了备件消耗的类型。通过忽略备件发生故障后维修时间或者订货供货时间,利用伽马分布的可加性建立备件的可用度评估模型。在此基础上,利用可修备件的可用度、可修备件的总费用为约束指标,构建以备件量最少为目标函数的多约束备件优化模型。在求解模型的过程中,利用拉格朗日乘子和边际优化启发式算法,对模型进行求解。算例中通过与仿真结果进行对比分析:当维修时间或者备件补充时间小于备件等效平均寿命三分之一时,平均误差小于5%,采用的近似度的方法是可行的。

Optimal inventory modeling for repairable spares under multi-constraints

For the widely existed problem of scrap for fault parts and spares storing under multi-constraints during the mission in the airport group, approximation method of availability evaluation and spares optimization is proposed. First, after analyzing the type of the spare parts consumption, the evaluation model of availability is obtained based on the additive property of Gamma distribution by omitting the maintenance time or the order delivery time. Afterwards, the optimization model of spares is built with the lowest quantity of spare parts under constraints of availability and cost. The Heuristic algorithm including Lagrange factors and marginal algorithm which is used to adjust the parameter dynamically are introduced during the model solving. In actual example compared with simulation results, the approximation method is reasonable and feasible when maintenance time is less than one third of the equivalent average life, which makes the average error less than 5%. The result shows that the approximation method of availability evaluation is reasonable.