Performance Analysis of Demand Planning Approaches for Aggregating, Forecasting and Disaggregating Interrelated Demands

• Main Authors: ChunHung Lan, 藍俊宏
• Other Authors: Argon Chen
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/05162183738272885732

碩士 === 國立臺灣大學 === 工業工程學研究所 === 90 === Results of demand planning serve as the basis of every planning activity in a demand-supply network and ultimately determine the effectiveness of manufacturing and logistic operations in the network. The uncertainty of demand signals, that are propagated and magnified over the network, becomes the crucial cause of ineffective operation plans. To manage the demand variability, appropriate demand aggregation and statistical forecasting approaches are known to be effective. In this research, we focus on a common demand planning approach where an aggregated demand is first forecasted and then disaggregated to forecasts for individual demands. The bivariate VAR(1) time series model will be used to simulate two interrelated demands. A very important finding of our research is that disaggregation of a forecasted aggregated demand is not effective in most cases and should be employed only when 1.predictable trends of two demands are similar; 2.correlation of two demands is positive and strong; 3.the two original CV’s are close and the CV’s after disaggregation are smaller than original CV’s.