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Paper proposal. Theme: The customer demand forecasting for E-SCM applications. Zhang Shuzhu. Background:. E-SCM Forecasting Bullwhip effect. Previous knowledge:. Longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in E-SCM;
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Paper proposal Theme: The customer demand forecasting for E-SCM applications Zhang Shuzhu
Background: • E-SCM • Forecasting • Bullwhip effect
Previous knowledge: • Longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in E-SCM; • Increased seasonality helps to reduce the bullwhip effect.
Assumptions: • A two-stage E-supply chain that consists of one supplier and one on-line retailer. • The supplier provides a single product for the on-line retailer, while the on-line retailer fulfills the requirements of the on-line customers at the marketplace through the distribution center.
Assumptions: 1.The actual customer demand emerges at the marketplace, and the retailer fulfills the customer demand by on-hand inventory, and any unfulfilled customer demands are backordered. here we suppose that retailer use (s, S) policy . s=LT*AVG + z*STD* √LT Q= √(2*K*AVG)/h S=Q + s 2. We assume that the supplier delivers all orders of the on-line retailer after a fixed lead time (L) so that it will simplify the retailer’s replenishment policy.
Basic simulated supply chain model We’ll try to find which kinds of parameters, methods, or factors can be used to keep the bullwhip ration low, while at the same time to increase forecast accuracy.