A global forecasting support system adapted to textile distribution

Competition and globalization imply a very accurate production and sourcing management of the Textile-Apparel-Distribution network actors. A sales forecasting system is required to respond to the versatile textile market and the needs of the distributor. Nowadays, the existing forecasting models are generally unsuitable to the textile industry. We propose a forecasting system, which is composed of several models and performs forecasts for various horizons and at different sales aggregation levels. This system is based on soft computing techniques such as fuzzy logic, neural networks and evolutionary procedures, permitting the processing of uncertain data. Performances of our models are then evaluated using the real data from an important French textile distributor.