AI 中文总结
研究在不断演变的预测误差分布下安全库存的不确定性估计问题，提出非参数方法，利用LOWDII评估历史误差影响，通过离散事件模拟验证，该方法能实现目标服务水平并降低平均库存，助企业转化预测改进为库存决策。
AI 中文摘要
我们开发了一种非参数方法来完善用于安全库存估计的预测误差历史，而不仅仅依赖于误差幅度或近期性。利用快速消费品环境中的预测误差数据，我们发现一年的误差不足以表征服务水平风险，而汇总数年存在问题，因为误差分布随时间变化。非参数年度比较表明偏差和离散度逐渐降低，这与预测过程中的学习一致。我们提出了LOWDII（留一法瓦瑟斯坦分布影响指数），它可以评估每个历史预测误差对用于安全库存校准的经验不确定性分布的分布影响。LOWDII识别出那些影响与其代表性不成比例的观测值，在不施加参数假设的情况下将瞬态失真与持续的尾部行为分开。我们在离散事件模拟中使用后续年份的需求实现作为验证来评估该方法。结果表明LOWDII实现了目标服务水平，同时相对于基准方法将平均库存降低了5.1%至22.6%。从管理角度来看，LOWDII帮助公司将预测过程中的改进转化为安全库存决策，避免将过时的历史误差投射到未来，并更早地捕捉到更低不确定性要求带来的经济效益。
英文摘要
We develop a non-parametric approach to refine forecast-error histories for safety stock estimation without relying on error magnitude or recency alone. Using forecast-error data from a fast-moving consumer goods environment, we show that one year of errors is insufficient to characterize service-level risk, while pooling several years is problematic because error distributions change over time. Non-parametric annual comparisons indicate a progressive reduction in bias and dispersion, consistent with learning in the forecasting process. We propose LOWDII (Leave-One-Out Wasserstein Distributional Influence Index), a diagnostic that evaluates the distributional influence of each historical forecast error on the empirical uncertainty distribution used for safety stock calibration. LOWDII identifies observations whose influence is disproportionate to their representativeness, separating transient distortions from persistent tail behaviour without imposing parametric assumptions. We evaluate the method in a discrete-event simulation using subsequent-year demand realizations as validation. The results show that LOWDII achieves the target service level while reducing average stock by 5.1% to 22.6% relative to benchmark methods. From a managerial perspective, LOWDII helps firms translate improvements in the forecasting process into safety stock decisions, avoiding the projection of obsolete historical errors into the future and capturing the economic benefit of lower uncertainty requirements earlier.
Comments34 pages, 2 figures
