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首页> 外文期刊>International Journal of Logistics: Research and Applications >Quantifying the Effect of Batch Size and Order Errors on the Bullwhip Effect Using Simulation
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Quantifying the Effect of Batch Size and Order Errors on the Bullwhip Effect Using Simulation

机译:使用仿真量化批次大小和订单错误对牛鞭效应的影响

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The bullwhip effect is the observed amplification in order-size variance for upstream nodes in a supply chain. Lee et al. (1997, Management Science, 43, pp. 546-558) identified four causes for a single-product demand: (1) nodes updating their forecasts independently; (2) order batching; (3) price fluctuations; and (4) rationing. Chen et al. (2000, Management Science, 46, 436-443) provided a lower bound of the impact of the first cause. We contribute by quantifying the impact of the other three causes individually through simulation. We require any order to be an integer multiple of the batch size and posit price fluctuations and rationing as causing random i.i.d. errors or deviations from the optimal order size. We find with high R2 that the increase in order variance over a "core" order variance (when none of the four causes is present) is directly proportional to the square of the batch size and to the variance of the order deviations.
机译:牛鞭效应是在供应链中上游节点观察到的订单大小差异的放大。 Lee等。 (1997年,管理科学,第43页,第546-558页)确定了单一产品需求的四个原因:(1)节点独立更新其预测; (2)订单分批; (三)价格波动; (4)配给。 Chen等。 (2000年,管理科学,46,436-443)提供了第一个原因的影响的下限。我们通过模拟分别量化其他三个原因的影响来做出贡献。我们要求任何订单都必须是批次大小的整数倍,并且假定价格波动和配给会导致随机i.i.d.错误或与最佳订单量的偏差。我们发现在R2较高的情况下,“核心”订单方差(当四个原因均不存在时)的订单方差的增加与批量大小的平方和订单方差的方差成正比。

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