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Paper progress

Paper progress. Theme: The customer demand forecasting for E-SCM applications. Zhang Shuzhu. Basic Structure:. Introduction Literature review Problem description Basic model and calculation ◇ forecasting( exponential smoothing method, Winter’s method, etc…) ◇ Bullwhip effect

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Paper progress

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  1. Paper progress Theme: The customer demand forecasting for E-SCM applications Zhang Shuzhu

  2. Basic Structure: • Introduction • Literature review • Problem description • Basic model and calculation • ◇ forecasting( exponential smoothing method, Winter’s method, etc…) • ◇ Bullwhip effect • ◇ Inventory policy • Experimental design and Output performance analysis • ◇ specify concrete parameters • ◇ Main effect • ◇ Interaction between different parameters • ◇ Future analysis • 6. Conclusion and future study

  3. 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.

  4. 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.

  5. Basic simulated supply chain model

  6. Flowchart of simulation model It is assumed that the online retailer has a linear demand process with seasonal swings.

  7. Generation of online customer demand and online retailer’s demand forecast Dt is the demand in week t, snormal() is a standard normal random number generator between 0 and 1. Base, slope and noise are typical linear demand parameters. Season represents magnitude of seasonality. Since both linear trend and seasonality exist together in the demand model, Winter’s method for forecasting is employed in the simulation model.

  8. Experimental design The purpose of the experimental design is twofold: • Analyzing the impact of the smoothing parameters, lead time, and strength of seasonality on the bullwhip effect. • Examining the interaction of the smoothing parameters with lead time and seasonality.

  9. Experiment design The bullwhip ratio is denoted as the dependent variables of the design of experiment. It indicates the ration of variance of the orders realized by the manufacturer to the variance of the demand observed by the retailers.

  10. thank you for your attentation

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