联系我们

论文查询结果	返回搜索

论文编号：	11333
作者编号：	2320170541
上传时间：	2019/12/12 11:54:03
中文题目：	基于关联规则挖掘和聚类分析的电力企业仓储货位优化研究
英文题目：	Research on Warehouse Slotting Optimization of Power Enterprise Based on Association Rule Mining and Clustering Analysis
指导老师：	张建勇
中文关键字：	电力企业仓储；货位优化；数据挖掘；关联规则；聚类分析
英文关键字：	Power Enterprise Warehouse; Slotting Optimization; Data Mining; Association Rules; Clustering Analysis
中文摘要：	电力物资管理是电力企业生产经营的战略性目标，是整个供应链管理的关键节点。电力物资管理能够保证电力行业生产建设的顺利实施，但是随着电力行业改革的深入，对电力企业仓储物流管理提出更高要求。因此，在整个电力行业领域，仓储配送管理短板日趋显现。为了应对这些难题，电力企业仓储的智能化决策与管理成为了电力公司仓储物流管理部门关注的焦点。 电力物资品类多、规格杂、专业性强、储存数量庞大等特性导致电力企业仓储物流中心物资运营数据相当复杂与庞大，难以单凭肉眼发现物资运营数据的潜在关系。然后随着仓储物流管理信息系统的开发和使用，使得电力物资运营数据得以大量积累，且随着大数据挖掘技术的发展，仓储物流中心更加注重其数据资源的价值，挖掘物流运作数据的价值成为其重要的市场竞争手段之一。 本文在分析电力物资仓储特征的基础上，提出了分类存储和定位存储相结合的两阶段电力物资货位优化策略。在此基础上，采用关联规则挖掘和聚类算法对电力企业仓储货位进行优化建模，并给出相应的模型求解算法；然后对S供电局电力物资货位优化进行应用分析，根据模型计算结果提出电力企业仓储物资货位管理的改进措施。
英文摘要：	Electric power material management is the strategic target of power company's production and management and the key node of whole supply chain management. Electric power material management can ensure smooth implementation of electric power industry production and construction, but with the deepening of electric power industry reform, put forward higher requirements for power material management. In order to cope with these problems, the intelligent decision and management of power storage has become the focus of the warehouse logistics management departments of power companies. The characteristics of many kinds of power materials, miscellaneous specifications, strong professionalism and large storage capacity have led to the complexity and huge data of the operation and logistics of the power storage and logistics center of the power enterprise. Then with the development and use of the warehousing logistics management information system, power material operation data can be accumulated in a large amount. Warehousing and logistics center pays more attention to the value of its data resources, and the value of mining logistics operation data becomes one of its important market competition means. Based on the analysis of the storage characteristics of electric power materials, this paper proposes a two-stage power material storage optimization strategy combining classification storage and location storage. On this basis, the association rule mining and clustering algorithm is used to optimize the modeling of the storage position of the power enterprise, and the corresponding model solving algorithm is given. Then the application analysis of the power material layout of the S power supply bureau is carried out and the model is calculated according to the model. The result is an improvement measure for the management of warehouse goods in power companies.
查看全文：	预览  下载(下载需要进行登录)