Beyzanur Çayır Ervural, İrem Uçal Sarı, Berk Koçyiğit

Kural tabanlı bulanık yaklaşımla talep tahmini ve hızlı tüketim sektöründe bir uygulama

Talep tahmin çalışmaları hem sektörel hem de akademik anlamda karar vericiler için önemli kabul edilen stratejik konulardan biridir. Sürekli değişen politik, kültürel, yasal ve ekonomik gelişmeler işletmeleri belirsizlik altında tahmin etmeye itmiştir. Karmaşık, çok boyutlu ve belirsizliğin yüksek olduğu ortamlarda klasik yöntemlerle problemleri modellemek oldukça güçtür. Bulanık yaklaşımlar daha esnek yapıda olduğu için daha kolay modelleme imkânı sağlamaktadır. Bu çalışmada hızlı tüketim sektöründe faaliyet gösteren bir firmanın talep tahmin çalışması, bulanık küme teorisi, bulanık eğer-ise kuralları ve bulanık çıkarım kavramlarına dayanan kural tabanlı bulanık mantık yaklaşımıyla ele alınmıştır. Kural tabanlı bulanık yaklaşımla elde edilen sonuçlar gerçekleşen değerler ile karşılaştırılmış ve düşük mutlak sapma değerlerine ulaşılmıştır. Ayrıca elde edilen sonuçlar zaman serileri yaklaşımıyla da karşılaştırılmış, yöntemlerin üstünlükleri gösterilmiştir.

Anahtar Kelimeler:

Talep tahmini, Bulanık mantık, Kural tabanlı bulanık yaklaşım

Fuzzy rule based demand forecasting and an application on fast moving consumer industry

Demand forecasting studies are one of the strategic issues which are considered as significant for academicians and decision makers. Constantly changing political, cultural, legal and economic developments have pushed the companies to predict under uncertainty. It is very difficult to model some problems with traditional methods in complex, multi-dimensional and highly uncertain environment. Fuzzy approaches provide an easier modelling owing to their flexible nature. In this study, a demand forecasting study in a FMCG (fast-moving consumer goods) company has been applied using a rule based fuzzy logic approach which utilizes fuzzy set theory, fuzzy if-else rules and fuzzy inference concepts. The obtained results have been compared with real demands and low MAPE (mean absolute percentage error) values have been calculated. Also the obtained results have been compared with time series approach and the superiorities of the methods are discussed.

Keywords:

Demand forecasting, Fuzzy logic, Rule based fuzzy approach,

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