考虑需求相关性的多巷道仓库货位分配问题  

Storage location assignment in a multi-aisle warehouse considering demand correlations

作　　者：肖建[1] 郑力[1] 

机构地区：[1]清华大学工业工程系,北京100084

出　　处：《计算机集成制造系统》2008年第12期2447-2451,共5页Computer Integrated Manufacturing Systems

基　　金：国家863计划资助项目(2008AA04Z102)~~

摘　　要：根据物料相关性及需求频率,建立了多巷道仓库中货位分配的优化数学模型。模型的优化目标是,既要尽量将关系密切的物料聚集摆放,又要尽量将需求频率高的物料靠近出入库口存储。为求解这一NP问题,提出一种结合启发式算法的混合遗传算法。数值实验表明,该模型与不考虑需求相关性的分配策略相比,可以得到更好的结果,并且随着需求相关性水平的提高,效果更加明显。By considering both material relevancy and requirement frequency, an optimization model for the storage location assignment in the multi-aisle warehouse was established. With the model, materials with closer relationships were compelled to be stored together closely, while at the same time, materials with high requirement frequen cy were stored close to the I/O point. A Hybrid Genetic Algorithm （HGA） was proposed to solve the NP problem. Numerical experiments showed that this model could obtain better results than other strategies without considering requirement correlations. As the level of demand correlations increased, the improvement was even more significant.

关 键 词：需求相关性 货位分配 模型 遗传算法 料单拣选 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]