Fuzzy forecast combiner design for fast fashion demand forecasting

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Yeşil, Engin and Kaya, Murat and Sıradağ, Sarven (2012) Fuzzy forecast combiner design for fast fashion demand forecasting. In: International Symposium on Innovations in Intelligent Systems and Applications (INISTA 2012), Trabzon, Turkey

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In this study, a combiner method is developed to create weekly demand forecasts for a fast-fashion apparel company. The combiner generates forecasts by combining the forecasts of three different methods through fuzzy logic. The combination weights are adaptive in the sense that the weights of the better-performing methods are increased over time. One of the three methods, which is based on product lifecycle, is relatively novel. This method is observed to be quite successful in forecasts as it can reflect the inherent regular seasonality of demand, and it allows the input of expert knowledge. The approach is illustrated through a simulation study that uses real (distorted) data from a Turkish apparel company. The combined forecast method is shown to be better than any of the methods alone.
Item Type: Papers in Conference Proceedings
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Manufacturing Systems Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Murat Kaya
Date Deposited: 09 Dec 2012 21:34
Last Modified: 26 Apr 2022 09:10
URI: https://research.sabanciuniv.edu/id/eprint/21258

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