TY - JOUR

T1 - On intermittent demand model optimisation and selection

AU - Kourentzes, Nikos

N1 - The final, definitive version of this article has been published in the Journal, International Journal of Production Economics 156, 2014, © ELSEVIER.

PY - 2014/10

Y1 - 2014/10

N2 - Intermittent demand time series involve items that are requested infrequently, resulting in sporadic demand. Croston's method and its variants have been proposed in the literature to address this forecasting problem. Recently other novel methods have appeared. Although the literature provides guidance on the suggested range for model parameters, a consistent and valid optimisation methodology is lacking. Growing evidence in the literature points against the use of conventional accuracy error metrics for model evaluation for intermittent demand time series. Consequently these may be inappropriate for parameter or model selection. This paper contributes to the discussion by evaluating a series of conventional time series error metrics, along with two novel ones for parameter optimisation for intermittent demand methods. The proposed metrics are found to not only perform best, but also provide consistent parameters with the literature, in contrast to conventional metrics. Furthermore, this work validates that employing different parameters for smoothing the non-zero demand and the inter-demand intervals of Croston's method and its variants is beneficial. The evaluated error metrics are considered for automatic model selection for each time series. Although they are found to perform similarly to theory driven model selection schemes, they fail to outperform single models substantially. These findings are validated using both out-of-sample forecast evaluation and inventory simulations.

AB - Intermittent demand time series involve items that are requested infrequently, resulting in sporadic demand. Croston's method and its variants have been proposed in the literature to address this forecasting problem. Recently other novel methods have appeared. Although the literature provides guidance on the suggested range for model parameters, a consistent and valid optimisation methodology is lacking. Growing evidence in the literature points against the use of conventional accuracy error metrics for model evaluation for intermittent demand time series. Consequently these may be inappropriate for parameter or model selection. This paper contributes to the discussion by evaluating a series of conventional time series error metrics, along with two novel ones for parameter optimisation for intermittent demand methods. The proposed metrics are found to not only perform best, but also provide consistent parameters with the literature, in contrast to conventional metrics. Furthermore, this work validates that employing different parameters for smoothing the non-zero demand and the inter-demand intervals of Croston's method and its variants is beneficial. The evaluated error metrics are considered for automatic model selection for each time series. Although they are found to perform similarly to theory driven model selection schemes, they fail to outperform single models substantially. These findings are validated using both out-of-sample forecast evaluation and inventory simulations.

KW - intermittent demand

KW - croston's method

KW - SBA method

KW - TSB method

KW - forecasting

KW - optimisation

KW - model selection

U2 - 10.1016/j.ijpe.2014.06.007

DO - 10.1016/j.ijpe.2014.06.007

M3 - Journal article

VL - 156

SP - 180

EP - 190

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

ER -