Abstract: The existing problems in equipment maintenance materiel storage support is analyzed at first, then adjusting supply is put forward to alleviate the problem of imbalanced resource storage, in which the over-stocked materiel is well used to satisfy the units lack of materiel. The multi objective decision-making model of equipment maintenance materiel adjusting supply is established, and simplified adopting [ε]-constraint method; the improved Particle Swarm Optimization algorithm（PSO） is designed based on guiding factor to solve the model, and verified through simulation experiment. The result shows that through adjusting supply the storage resources in the support system can be balanced effectively and the support efficiency of equipment maintenance materiel is enhanced as well.

Key words: equipment maintenance materiel, adjusting supply, decision-making, improved Particle Swarm Optimization（PSO）

摘要： 分析了装备维修器材存储保障存在的问题，提出采用调剂供应缓解存储保障的资源失衡问题，充分利用存储过剩的超储器材补充库存短缺的需求单位，建立了装备维修器材调剂供应的多目标决策模型，采用[ε]-约束法对模型进行处理，基于引导因子设计了改进的粒子群优化算法（Particle Swarm Optimization，PSO）对模型求解，并通过仿真实例进行了验证。结果表明，采用调剂供应的方式，可使保障系统内的资源存储得到有效的平衡，装备维修器材的保障效率也有所提高。

关键词: 装备维修器材, 调剂供应, 决策, 改进粒子群优化算法