摘要
针对货位分配模型在货物相关性指标计算中难以精确赋权的困境,结合偏序集理论提出了由权重顺序便可以对相关性进行运算的方法。以Z公司的成品酒仓库为研究对象,利用Apriori算法计算货品之间的相关性,在此基础上利用偏序分析方法对货品进行分类。综合考虑成品酒的出库频次、相关性和货架稳定等因素,建立了货位分配优化模型,并用遗传算法对模型进行求解,得到最终的货位分配方案。优化后的方案拣货效率提升,证明了该模型和算法的有效性。研究结论为降低企业仓储成本,提升仓储系统的拣选和配送效率提供参考。
Aiming at the dilemma that it is difficult to accurately assign weights in the calculation of cargo relevance indexes in the cargo allocation model,a method that can be used to calculate the relevance by the order of weights is proposed by combining with the theory of partial order set.Taking Company Z's finished wine warehouse as the research object e,the Apriori algorithm is used to calculate the correlation between goods,and on the basis of which the partial order analysis method is used to classify the goods.Considering the frequency of finished wines,correlation and shelf stability,a space allocation optimization model is established,and the model is solved by genetic algorithm to obtain the final space allocation scheme.The study shows that the optimized scheme improves the picking efficiency,which proves the effectiveness of the model and algorithm.The conclusions of the study provide reference for reducing the cost of enterprise warehousing and improving the picking and distribution efficiency of the warehousing system.
作者
刘金梅
岳立柱
LIU Jinmei;YUE Lizhu(School of Business Administration,Liaoning Technical University,Huludao 125105,China)
出处
《辽宁工程技术大学学报（社会科学版）》
2024年第4期273-281,共9页
Journal of Liaoning Technical University(Social Science Edition)
基金
安徽省社会科学创新发展研究课题(2023CX085)。
关键词
货位分配
偏序分析
仓储系统
APRIORI算法
遗传算法
location allocation
partial order analysis
warehousing system
Apriori algorithm
genetic algorithm
