A short and mean-term automatic forecasting system – application to textile logistics

A short and mean-term automatic forecasting system – application to textile logistics

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Article ID: iaor20052922
Country: Netherlands
Volume: 161
Issue: 1
Start Page Number: 278
End Page Number: 284
Publication Date: Feb 2005
Journal: European Journal of Operational Research
Authors: , ,
Keywords: distribution, fuzzy sets
Abstract:

In order to reduce their stocks and to limit stock out, textile companies require specific and accurate sale forecasting systems. More especially, textile distribution involves different forecast lead times: mean-term (one year) and short-term (one week in average). This paper presents two new complementary forecasting models, appropriate to textile market requirements. The first model (AHFCCX) allows to automatically obtain mean-term forecasting by using fuzzy techniques to quantify influence of explanatory variables. The second one (SAMANFIS), based on a neuro-fuzzy method, performs short-term forecasting by readjusting mean-term model forecasts from load real sales. To evaluate forecasts accuracy, our models and classical ones are compared to 322 real items sales series of an important ready to wear distributor.

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