摘要
文章研究了联合计划、预测和补货(CPFR)中的联合预测流程,并建立了相关的预测模型。在建模的过程中,使用了状态空间方程来描述实际市场需求和观测到的市场需求(销售量),并通过卡尔曼滤波来预测零售商下期的销售量,结合零售商库存策略,预测出零售商下期的订单量。
This paper focuses on collaborative forecasting process of collaborative planning, forecasting and replenishment （CPFR） and establishes a forecasting model. This model applies state-space equation to describe actual market demand and observed market demand （sales）, uses Kalman filter to forecast retailers＂ sales in the next period, and predicts retailers＂ orders as well.
出处
《物流科技》
2009年第2期137-139,共3页
Logistics Sci-Tech
关键词
联合计划
预测和补货
联合预测
状态空间方程
卡尔曼滤波
collaborative planning
forecasting and replenishment
collaborative forecasting
state-space equation
Kalman filter
