计算机与现代化 ›› 2009, Vol. 1 ›› Issue (11): 30-32.doi:

• 算法 • 上一篇    下一篇

基于模糊聚类算法的备件需求辨识模型

郝方平, 汪家常   

  1. 安徽工业大学管理科学与工程学院,安徽 马鞍山 243002
  • 收稿日期:2009-08-05 修回日期:1900-01-01 出版日期:2009-11-30 发布日期:2009-11-30

Model of Spare Parts Demand Identification Based on Fuzzy Clustering Algorithm

HAO Fang-ping,WANG Jia-chang   

  1. School of Management Science and Engineering, Anhui University of Technology, Ma’anshan 243002, China
  • Received:2009-08-05 Revised:1900-01-01 Online:2009-11-30 Published:2009-11-30

摘要: 钢铁企业物料系统中的备件种类是极其复杂的,其需求的影响因素也是很多的,因此备件的需求计划很难确定。本文针对钢铁企业内部的备件需求计划问题,利用模糊ISODATA算法,对影响备件采购的因素进行模糊聚类,确定每个备件在每类影响因素上的隶属度,并利用仿真实验验证算法的可行性,从而精确确定每个备件的最重要影响因素类别,为下一步建立需求计划模型提供依据。

关键词: 备件, 需求计划模型, ISODATA算法

Abstract:

The species of spare parts in material system of Iron and steel enterprise are very complex, also there are many influent factors on demand, so it’s very difficult to ensure the requirement planning of spare parts. According to the problem of spare parts requirement planning in iron and steel enterprise’s internal, using fuzzy ISODATA algorithm to fuzzy clustering in the influent factors of spare parts purchasing, then, ensuring the membership degree in every kind of influent factor of every spare parts, and using simulation results to verify the feasibility of algorithm, thus, it can accurately determine the most important influent factors’ kind in order to provide evidence for building the model of requirement planning of spare parts.

Key words: spare parts, requirement planning model, ISODATA algorithm