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All-zero forecasts for lumpy demand: a factorial study

机译:集总需求的全零预测:析因研究

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Lumpy demand is a phenomenon encountered in manufacturing or retailing when the items are slow-moving or too expensive, for example fighter plane engines. So far, the seminal procedure of Croston's (1972), with or without modifications, has been the preference for forecasting lumpy demand. Nevertheless, Croston (1974) and others, such as Venkitachalam et al. (2002), have suggested the use of zero forecasts when the demand contains many zeros. In this paper, we put to the test this idea by doing a full factorial study comparing five forecasting methods, including all-zero, under several levels of demand lumpiness, demand variation and ordering, holding and shortage cost. We evaluate the forecasting methods by three measures of forecast error and two measures of inventory cost. We find that all-zero forecasts yield the lowest cost when lumpiness is high; is it also best for mid-lumpiness, if the shortage cost is much higher than the holding cost. We also find that the lowest forecasting error does not necessarily lead to the lowest system cost. And contrary to the assertions in Chen et al. (2000b) and Dejonckheere et al. (2003, 2004), our factorial experiment reinforces the intuition that simple exponential smoothing is superior to an equivalent moving average.
机译:需求不旺是一种制造或零售过程中遇到的现象,例如战斗机发动机等物品移动缓慢或价格过高。到目前为止,Croston(1972)的开创性程序(无论是否进行了修改)一直是预测块状需求的首选方法。尽管如此,Croston(1974)和其他人,例如Venkitachalam等。 (2002年)建议当需求包含许多零时使用零预测。在本文中,我们通过进行全面析因研究,在五个层​​次的需求集总,需求变化和订购,持有和短缺成本水平下,比较了包括全零在内的五种预测方法,对这一思想进行了检验。我们通过预测误差的三种方法和库存成本的两种方法来评估预测方法。我们发现,在高块率的情况下,全零预测产生的成本最低;如果短缺成本比持有成本高得多,那么这对于中等胖度也是最好的。我们还发现,最低的预测误差不一定会导致最低的系统成本。与陈等人的主张相反。 (2000b)和Dejonckheere等。 (2003,2004),我们的阶乘实验增强了直觉,即简单的指数平滑优于等效的移动平均值。

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