基于密度峰值聚类方法的多准则ABC库存分类模型

doi:10.3969/j.issn.1674-9499.2024.06.018

	基于密度峰值聚类方法的多准则ABC库存分类模型
其他题名	Multi-Criteria ABC Inventory Classification Model Based on Density Peak Clustering Method
	刘文杰1 ; 杨海军1 ; 杨硕 2; 秦伟德1
	2024-06-25
发表期刊	黑河学院学报
卷号	15 期号:6 页码:67-71
摘要	对于ABC库存分类管理的多准则优化问题,已有多种分类模型被提出,其中无监督机器学习方法具有吸引人的理论和实践特性,最大优点是不涉及主观性.在平均单位成本、全年货币使用量和提前期这三种库存决策要素的基础上,提出一个基于密度峰值聚类方法的多准则ABC库存分类模型.使用DPC模型和K-Means 模型对由47个库存单位组成的标准数据集进行聚类分类,利用成本-服务绩效方法将DPC模型、K-Means 模型和GMM模型分类结果进行比较分析.研究结果表明,在成本-服务绩效方面,DPC模型优于K-Means 模型和GMM模型,同时发现这三个无监督聚类模型分类结果优于使用同一数据集的几种数学规划模型.
其他摘要	For addressing the multi-criteria optimization problem of ABC inventory classification management,a variety of classification models have been proposed.Among them,the unsupervised machine learning method has attractive theoretical and practical characteristics,and its biggest advantage is that it does not involve subjectivity.Based on three inventory decision-making elements:average unit cost,annual currency usage and lead time,a multi-criteria ABC inventory classification model is proposed based on the density peak clustering method.This paper studies the performance and effectiveness of the comparison model by using the DPC model and the K-Means model,clusters and classifies the standard data set composed of 47 inventory units,classifies the DPC model,K-Means model and GMM using the cost-service performance method,and compares and analyzes the model classification results.The research results show that in terms of cost-service performance,the DPC model is superior to the K-Means model and the GMM model.At the same time,it is found that the classification results of these three unsupervised clustering models are better than several mathematical programming models using the same data set.
关键词	库存分类多准则ABC库存分类 DPC K-Means 无监督聚类算法
DOI	10.3969/j.issn.1674-9499.2024.06.018
URL	查看原文
ISSN	1674-9499
语种	中文
原始文献类型	Periodical
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/37364
专题	信息工程与人工智能学院
作者单位	1.兰州财经大学信息工程学院,甘肃兰州 620020; 2.普华永道中天会计师事务所,天津 300051
第一作者单位	信息工程与人工智能学院
推荐引用方式 GB/T 7714	刘文杰,杨海军,杨硕,等. 基于密度峰值聚类方法的多准则ABC库存分类模型[J]. 黑河学院学报,2024,15(6):67-71.
APA	刘文杰,杨海军,杨硕,&秦伟德.(2024).基于密度峰值聚类方法的多准则ABC库存分类模型.黑河学院学报,15(6),67-71.
MLA	刘文杰,et al."基于密度峰值聚类方法的多准则ABC库存分类模型".黑河学院学报 15.6(2024):67-71.