摘要
针对在动车组检修作业中需要大量使用的油脂化工类备品的仓储管理问题,提出了一种在动车段仓库中应用RFID技术获取实时信息及利用遗传算法对仓储过程进行优化的仓库-库区-货位仓储管理模式。通过分析油脂化工类备品的特殊性及约束条件等问题,进而建立其仓储过程的数学模型,并用遗传算法对模型进行求解。仿真数据显示,这种仓储管理模式在提升仓库的空间利用率及备品的出入库效率方面具有良好的效果,保障了油脂化工类备品在仓储过程中的有效性、高效性及安全性,间接提升了动车组检修作业效率,为高速铁路的安全高效运营提供了后备保障。
In order to solve the storage problem of oil chemical products which are widely used to repair EMU trains, we put forward a warehouse - area - space management mode combined with RFID technology and genetic al- gorithm. By analyzing the peculiarity and constraint of oil chemical, we established a mathematic model for the stor- age process, and finally solved the model with genetic algorithm. The experimental results and analysis show that this model has excellent effect in promoting the utility rate of space and input - output efficiency of oil chemical. This way can be used to improve the process of storage in EMU depot, guarantees the effectiveness, high efficiency and security of oil chemical products storage, and also enhances the working performance of EMU repair and guarantees opera- tion of high speed railway.
作者
程凯
张惟皎
CHENG Kai;ZHANG Wei - jiao(China Academy of Railway Sciences, Beijing 100081, China;Institute of Computing Technology, China Academy of Railway Sciences,Beijing 100081, China)
出处
《计算机仿真》
北大核心
2018年第4期362-366,共5页
Computer Simulation
基金
中国铁路总公司科技研究开发计划(2015J006-A)
关键词
动车段
油脂化工
仓储管理
遗传算法
EMU depot
Oil chemical
Warehouse management
Genetic algorithm
