Title: An empirical investigation of comparative performance of approximate and exact corrections of the bias in Croston's method in forecasting lumpy demand
Authors: Adriano O. Solis; Francesco Longo; Somnath Mukhopadhyay; Letizia Nicoletti
Addresses: School of Administrative Studies, York University, Toronto, Ontario M3J 1P3, Canada ' Department of Mechanical, Energy, and Management Engineering, University of Calabria, 87036 Rende, Cosenza, Italy ' Marketing and Management Department, College of Business Administration, The University of Texas at El Paso, El Paso, Texas 79912, USA ' Cal-Tek Srl, Via Spagna 70, 87036 Rende, Cosenza, Italy
Abstract: A positive bias in Croston's method, which had been developed to forecast intermittent demand, was reported by Syntetos and Boylan (2001). They proposed an approximate correction. Subsequently, Shale et al. (2006) proposed an 'exact' correction. Both corrections were derived analytically. The mathematical analysis establishes the superiority of the exact correction over both Croston's method and the approximate correction. We empirically investigate whether or not there are significant improvements in statistical forecast accuracy as well as inventory control performance obtained by applying the approximate or exact correction when forecasting lumpy demand. Using extensive simulation experiments, we find overall superior forecast accuracy of the bias correction methods over both simple exponential smoothing and Croston's methods. However, the exact correction yielded the same or only marginally better accuracy measures compared with the approximate correction. Moreover, in terms of inventory control performance, we observe marginal differences in inventory on hand and backlogs.
Keywords: forecasting; time series; inventory; modelling and simulation; lumpy demand.
International Journal of Simulation and Process Modelling, 2017 Vol.12 No.6, pp.535 - 550
Received: 12 Jun 2016
Accepted: 16 Jan 2017
Published online: 23 Jan 2018 *