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On ordering adjustment policy under rolling forecast in supply chain planning

机译:供应链计划中滚动预测下的订货调整策略

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Rolling forecast is a useful tool for lowering total cost with regard to practical inventory management. The details regarding a rolling forecast are obtained from a customer's projected ordering data. The customer estimation of a rolling forecast may deviate from actual orders because of unstable conditions or customer's deliberation. This study investigates what measures a customer might apply in responding to a situation where the rolling forecast deviates from the actual order. In addition, an appropriate ordering adjustment policy is proposed for better monitoring the supply chain performance with regard to a variant level of error concerning rolling forecast data. This study also considers the influence of lead time and inventory cost structure. We adopted a simulation approach, employing a model developed and examined in several different settings. The proposed ordering adjustment policies are determined by AVG, SD, and RMSE calculated from differences existing between historical forecasts and realized data. Levels of estimate error and estimate bias in a rolling forecast are included in the experimental procedure. Results reveal that the RMSE ordering adjustment policy is the most effective in situations of normal and downside estimation bias, whereas the AVG policy is more appropriate in the case of upside estimation bias. The level of estimation error is irrelevant to the selection of ordering adjustment policies, but it is positively associated with inventory costs. Stock-out costs and lead time are positively associated with inventory costs. Accuracy of the rolling forecast is therefore deemed to be essential in a situation involving a long lead time with high stock-out costs.
机译:滚动预测是降低实际库存管理总成本的有用工具。有关滚动预测的详细信息可从客户的预计订购数据中获得。由于不稳定的条件或客户的考虑,客户对滚动预测的估计可能会与实际订单有所不同。这项研究调查了客户在应对滚动预测偏离实际订单的情况时可能采取的措施。此外,提出了适当的订购调整策略,以针对与滚动预测数据有关的变量的不同水平更好地监视供应链绩效。本研究还考虑了交货时间和库存成本结构的影响。我们采用了一种仿真方法,采用了在几种不同设置下开发和检查的模型。建议的订购调整策略由AVG,SD和RMSE(根据历史预测和实际数据之间的差异计算得出)确定。实验过程中包括滚动预测中的估计误差和估计偏差水平。结果表明,在正常和下行估计偏差的情况下,RMSE排序调整策略是最有效的,而在上行估计偏差的情况下,AVG策略更合适。估计误差的水平与订购调整策略的选择无关,但与库存成本成正相关。缺货成本和提前期与库存成本正相关。因此,在涉及交货时间长,缺货成本高的情况下,滚动预测的准确性至关重要。

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