摘要
在物流管理中运输问题非常重要,物资要实现实体转移,都需要通过运输来实现;而要达到运输费用的最小,必须使物资的需求具有前瞻性。根据现代经济学中的预测方法,结合企业物资历年实际需求情况,运用时间序列的趋势移动平均法、自适应滤波预测法、灰色预测法,利用层次分析法确定相应的权重后对未来物资需求进行组合预测,并应用于物资运输管理中,使运输费用达到最小,从而使运输管理更具有现实性及可操作性。
In logistics, transportation is very important. Transportation can make materials move. In order to minimize transportation cost, requirement of materials must be frontal. In this paper trend moving average method, self-adaptive filtering forecast method and grey prediction method are combined with weights determined by analytic hierarchy process method and used to determine the preferred material need decision in a supply chain management. The result from a real-world case study is encouraging. The method is used in the transportation model in order to make its cost as low as possible, and so transportation management has more actuality and operability than ever.
出处
《工业工程》
2007年第3期102-106,共5页
Industrial Engineering Journal
关键词
时间序列
移动平均法
自适应滤波法
灰色预测法
层次分析法
组合预测
运输管理
time series
moving average method
self-adaptive filtering method
grey prediction method
analytic hierarchy process
combined forecast
transportation model
