摘要
在仓储配送中心常见的"波次拣货、整体补货"的分区拣选环境中,为减少整体作业时间,基于谱聚类(spectral clustering,SC)算法及货位指派规则,提出了综合考虑物料需求关联与周转率的货位优化方法。构建了物料关联性计算模型、物料相似性度量模型、聚合类存储优化模型及物料存储优化模型,通过肘方法确定聚类的最佳簇数后,在基于拉普拉斯矩阵分解的SC算法中引入KMeans++算法对物料进行聚类,以降低初始聚类中心点选择的随机性,最后基于货位指派规则对聚合类及货位的布局进行优化调整。试验结果表明,考虑物料需求关联与周转率的货位优化方法,不仅能够有效缩短订单拣选路径,而且可以提高订单拣选效率。
In the district picking environment of“wave picking,overall replenishment”,which is common in warehousing and distribution centers,a location optimization method based on spectral clustering(SC)algorithm and rules of location assignment is proposed,which considers material demand correlation and turnover rate comprehensively to reduce the overall working time.The material correlation calculation model,material similarity measurement model,aggregate storage optimization model and material storage optimization model are constructed.After determining the optimal cluster number of clustering by elbow method,spectral clustering based on Laplacian matrix decomposition is constructed.The K-Means++algorithm is introduced into the SC algorithm to cluster the materials to reduce the randomness of the initial cluster center point selection.Finally,based on the location assignment rules,the layout of the aggregation class and the location is optimized.The test results show that the location optimization method considering the material demand correlation and turnover rate,can short the order picking path effectively and improve the order picking efficiency.
作者
周亚云
项前
余崇贵
陈东
管树林
ZHOU Yayun;XIANG Qian;YU Chonggui;CHEN Dong;GUAN Shulin(College of Mechanical Engineering,Donghua University,Shanghai 201620,China;Shanghai Aviation Industrial(Group)Co.Ltd.,Shanghai 200232,China;Shanghai Jingxing Logistics Equipment Engineering Co.Ltd.,Shanghai 201611,China;Shanghai Jingxing Storage Equipment Engineering Co.Ltd.,Shanghai 201108,China)
出处
《东华大学学报（自然科学版）》
CAS
北大核心
2020年第3期414-420,共7页
Journal of Donghua University(Natural Science)
基金
上海仓储物流设备工程技术研究中心能力提升计划资助项目(17DZ2283800)
上海市松江区产业转型升级发展专项资金重点领域示范应用资助项目(201801)
上海市闵行区科委重大科技攻关资助项目(2017MH205)。
关键词
货位优化
需求关联
周转率
谱聚类算法
指派规则
location optimization
demand correlation
turnover rate
spectral clustering algorithm
assignment rules
