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: | Happiette Michel, Thomassey Sbastien, Castelain Jean Marie |
Keywords: | distribution, fuzzy sets |
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.