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Fuzzy Forecast Combining for Apparel Demand Forecasting

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Intelligent Fashion Forecasting Systems: Models and Applications

Abstract

In this chapter, we present a novel approach for apparel demand forecasting that constitutes a main ingredient for a decision support system we designed. Our contribution is twofold. First, we develop a method that generates forecasts based on the inherent seasonal demand pattern at product category level. This pattern is identified by estimating lost sales and the effects of special events and pricing on demand. The method also allows easy integration of product managers’ qualitative information on factors that may affect demand. Second, we develop a fuzzy forecast combiner. The combiner calculates the final forecast using a weighted average of forecasts generated by independent methods. Combination weights are adaptive in the sense that the weights of the better-performing methods are increased over time. Forecast combination operations employ fuzzy logic. We illustrate our approach with a simulation study that uses data from a Turkish apparel firm.

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Acknowledgements

This study was supported by TÜBİTAK (The Scientific and Technological Research Council of Turkey) TEYDEB Industrial Research Funding Program Grant Numbers 7100373 and 7110387, awarded to GETRON Bilişim Hizmetleri A. Ş. The authors also wish to thank Murat Ercan, Bülent Göven, Gökhan Çetin and COŞKUN HAZIR GİYİM A.Ş. (SÜVARİ) for their help in preparing this chapter.

Author information

Authors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, 34956, Turkey

    Murat Kaya

  2. Faculty of Electrical and Electronics Engineering, Department of Control Engineering, Istanbul Technical University, Maslak, TR-34469, Istanbul, Turkey

    Engin Yeşil & M. Furkan Dodurka

  3. Getron Bilişim Hizmetleri A.ş, Yıldız Teknik Üniversitesi Davutpaşa Kampüsü, Teknopark Binası B1 Blok, Esenler, 34220, Istanbul, Turkey

    Sarven Sıradağ

Authors
  1. Murat Kaya
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  2. Engin Yeşil
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  3. M. Furkan Dodurka
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  4. Sarven Sıradağ
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Corresponding author

Correspondence to Murat Kaya .

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Editors and Affiliations

  1. Business Division Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hongkong, People's Republic of China

    Tsan-Ming Choi

  2. Business Division Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hongkong, People's Republic of China

    Chi-Leung Hui

  3. Business Division Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hongkong, People's Republic of China

    Yong Yu

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Kaya, M., Yeşil, E., Dodurka, M.F., Sıradağ, S. (2014). Fuzzy Forecast Combining for Apparel Demand Forecasting. In: Choi, TM., Hui, CL., Yu, Y. (eds) Intelligent Fashion Forecasting Systems: Models and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39869-8_7

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