摘要
Spare parts are critical to scheduled maintenance and fault repair, and can directly affect the readiness and combat capability of equipment. Equipmentrs capacity of carrying spares is influenced by its storage space and scales, so it is necessary to consider economic factors, e.g. spares cost, as well as non-economic ones, such as spares volume, mass and scale, when optimizing spares configuration. Aiming at this problem, the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis. Through the introduction of Lagrange factors, the spares cost is transformed to shadow price, and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed. The result of a given example is analyzed, and demonstrates that the proposed model can be optimized with all constraints, and the research can provide a new way for carrying spares optimization.
Spare parts are critical to scheduled maintenance and fault repair,and can directly affect the readiness and combat capability of equipment.Equipment′s capacity of carrying spares is influenced by its storage space and scales,so it is necessary to consider economic factors,e.g.spares cost,as well as non-economic ones,such as spares volume,mass and scale,when optimizing spares configuration.Aiming at this problem,the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis.Through the introduction of Lagrange factors,the spares cost is transformed to shadow price,and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed.The result of a given example is analyzed,and demonstrates that the proposed model can be optimized with all constraints,and the research can provide a new way for carrying spares optimization.
基金
supported in part by the General Armament Department Pre-research Foundation in 12th FiveYear(No.51304010206)
the National Defense Pre-research Project in 13th Five-Year (No.41404050502)