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The development of a hierarchical forecasting method for predicting spare parts demand in the South Korean Navy

Lookup NU author(s): Seong Moon, Professor Christian Hicks, Dr Andrew Simpson



In the South Korean Navy the demand for many spare parts is infrequent and the volume of items required is irregular. This pattern, known as non-normal demand, makes forecasting difficult. This paper uses data obtained from the South Korean Navy to compare the performance of various forecasting methods that use hierarchical and direct forecasting strategies for predicting the demand for spare parts. A simple combination of exponential smoothing models was found to minimise forecasting errors. A simulation experiment verified that this approach also minimised inventory costs.

Publication metadata

Author(s): Moon S, Hicks C, Simpson A

Editor(s): Grubbstrom RW; Hinterhuber HH

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Sixteenth International Working Seminar on Production Economics

Year of Conference: 2010

Number of Volumes: 4

Pages: 385-398

Date deposited: 11/03/2010