不完全维修条件下的备件多级库存优化

Multi-echelon inventory optimization of spare parts under imperfect maintenance conditions

考虑到不完全维修条件下有限维修次数的约束,研究含有报废流程的可修件多级库存优化问题。以可维修备件多级管理技术模型为基础,以可用度为约束条件,以系统费用为优化目标,引入报废流程,建立多保障等级多装备层次的库存优化模型;在算法设计上提出了粒子群—边际禁忌混合算法,算法前期使用粒子群算法求解,以便快速得到全局优质解,后期进入禁忌搜索以开发局部搜索能力,并利用边际优化算法构造邻域,从而求得最优解。多个实验结果表明,所建模型正确有效,所提算法在解决备件多级库存优化问题上具有一定的优越性。

Considering the constraints of limited maintenance times under imperfect maintenance conditions,the multi-echelon inventory optimization problem of repairable spare parts with scrap process was studied.Based on METRIC model,a multi-echelon inventory optimization model with scrap process was established with the constraint of availability and the optimization goal of costs.In the algorithm design,a Particle Swarm Optimization-Marginal Tabu Search(PSO-MTS)hybrid Algorithm was proposed.In the early stage of the algorithm,PSO algorithm was used to obtain the global high-quality solution quickly,then Tabu Search was entered to develop the local search ability,and the marginal optimization algorithm was used to construct the neighborhood to obtain the optimal solution.The experiment results showed that the proposed approach could solve the multi-echelon inventory optimization problem of spare parts effectively.