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计算机工程 ›› 2010, Vol. 36 ›› Issue (15): 66-67,71. doi: 10.3969/j.issn.1000-3428.2010.15.023

• 软件技术与数据库 • 上一篇    下一篇

基于数据场和云模型的物料需求计划方法

李新建,刘启华   

  1. (武汉大学信息管理学院,武汉 430072)
  • 出版日期:2010-08-05 发布日期:2010-08-25
  • 作者简介:李新建(1969-),男,博士研究生,主研方向:电子商务,供应链管理;刘启华,博士研究生

Material Requirement Planning Method Based on Data Field and Cloud Model

LI Xin-jian, LIU Qi-hua   

  1. (School of Information Management, Wuhan University, Wuhan 430072)
  • Online:2010-08-05 Published:2010-08-25

摘要: 为在供应链物料需求计划中自动发现重要材料,基于数据场和云模型提出物料需求计划方法。数据场聚类方法基于场中自然嵌套数据结构等势线(面)的分布以及数据对象自组织的聚集特征实现水平划分。借助数据场,材料能自动聚类并在物料需求计划中发现不同分类。通过云模型反映聚类知识的不确定性,尤其是随机性和模糊性。实例研究结果表明,该方法可以用于供应链物料需求计划领域。

关键词: 数据场, 云模型, 物料需求计划, 聚类分析

Abstract: To find out the important materials automatically in supply chain Material Requirement Planning(MRP), this paper proposes a material requirement planning method based on data field and cloud model. The data field clustering method is based on the distribution of equipotential line (surface) of the natural nested data structures in the field and the aggregation properties of self-organization among data objects to achieve the level division. By means of data field, the materials can be clustered automatically and find out different kinds of classifications in material requirement planning. Cloud model can reflect the uncertainty of clustering knowledge, especially the randomness and fuzziness. An actual case study and its results analysis show that this approach is feasible in the area of supply chain material requirement planning.

Key words: data field, cloud model, Material Requirement Planning(MRP), clustering analysis

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