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首页> 外文期刊>The Journal of the Textile Institute. Part 3, Managing Supply Chains >A Short and Mean Term Forecasting System Adapted to Textile Items' Sales
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A Short and Mean Term Forecasting System Adapted to Textile Items' Sales

机译：适应纺织品销售的短期和中长期预测系统

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摘要

To reduce their stocks and to limit stockouts, textile companies must improve their supply chain management. This requires sales' forecasting systems adapted to the uncertain environment of the textile field. In addition, with the delivery constraint, textile distribution requires different forecast lead times: mean term (one season) and short term (three weeks on average). Thus, the proposed system is composed of two complementary forecasting models. The first model (AHFCCX), which has been developed in previous work, allows a textile company to obtain mean term forecasting to pass commands to providers; this model uses the technique of fuzzy logic to quantify the influence of system variables. The second model (SAMANN) is based on neural networks, and performs short term forecasting by modifying the results of previous model forecasting from real sales data. To evaluate the accuracy of forecasting, our models and classical ones are compared using real sales data from an important ready-to-wear distributor.
机译：为了减少库存并限制库存，纺织公司必须改善其供应链管理。这需要适合纺织领域不确定环境的销售预测系统。此外，由于交货条件的限制，纺织品分销需要不同的预测交货时间：平均期限（一个季节）和短期（平均三周）。因此，所提出的系统由两个互补的预测模型组成。第一个模型（AHFCCX）是在先前的工作中开发的，它允许纺织公司获得均值预测，以将命令传递给提供商。该模型使用模糊逻辑技术来量化系统变量的影响。第二个模型（SAMANN）基于神经网络，并通过修改来自实际销售数据的先前模型预测的结果来执行短期预测。为了评估预测的准确性，我们使用来自重要成衣分销商的实际销售数据来比较我们的模型和经典模型。

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