This thesis considers an important phenomenon: the bullwhip effect - the amplification of variability of demand as one moves up a supply chain. We apply Agent-Based Modeling (ABM) at the macro level of our system to build relationships among the trading partners; and then we utilize system dynamics to model rules like ordering policy or inventory management at the micro level. We define these rules according to Sterman's generic stock acquisition and ordering heuristic in his Beer Distribution Game Model (Sterman 1989, 321-339). By including additional forecasting methods like moving average, Holts, and double exponential smoothing (DES) method, we extend the model to investigate how different ordering policies and forecasting methods affect the bullwhip effect. Through simulations in the ordering policy space, we demonstrate that fed with a local trend customer order pattern, the bullwhip effect can be mitigated significantly if the suitable forecasting method like Holts or DES is applied under the right ordering policy that has a slow adjustment to the discrepancy of the stock. Comparing with previous research, we extend Sterman's model to investigate what other managerial behaviours, like the aggregation effect, the varied ordering policy and additional forecasting methods would bring to the bullwhip effect. In the "smoothing" method, we extend the moving average and exponential average, which appeared in Forrester's study (Forrester 1961), to Holts and DES method. In modeling, we differ from CDRS (Chen, Drezener, Ryan, and Simchi-Levi 2000, 436-443) and CRS (Chen, Ryan, and Simchi-Levi 2000, 269-286) and Yao (2001) by replacing order-up-to policy with the heuristic ordering policy. Our research has another important managerial insight: through the right ordering policy and forecasting method, trading partners can alleviate the bullwhip effect without adopting information sharing, which may lead to other problems, like mutual trust or additional cost.
Key words. Supply chain management; Bullwhip Effect; System dynamics; Agent-Based Modeling; Forecasting.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/27431 |
| Date | January 2006 |
| Creators | Yuan, Xin |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 118 p. |
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