FORECASTING INTERMITTENT DEMAND WITH ARTIFICIAL NEURAL NETWORKS METHOD

Yıl 2016, , 1 - 32, 01.06.2016

Derya Saatçioğlu Necdet Özçakar

https://doi.org/10.14514/BYK.m.21478082.2016.4/1.1-32

Cited By: 3

Öz

Forecasting and accuracy of demand has a direct effect in the success of a business and customer satisfaction. Whereas many methods show successful results in forecasting and planning demand of products with smooth demand, they fail with products that have many time periods with zero demands. Variability of capacity and pattern of demand causes forecasting and planning of it to become difficult. In this study, for forecasting intermittent demand, Croston Method and Multilayer Perceptron which is also an artificial neural network have been analyzed. These methods have been used for forecasting intermittent demand in one of the categories of a business that operates in e-trade sector. Afterwards, performance of each method has been compared using appropriate accuracy measures

Anahtar Kelimeler

Intermittent demand, multilayer perceptron, artificial neural networks

YAPAY SİNİR AĞLARI YÖNTEMİ İLE ARALIKLI TALEP TAHMİNİ

Öz

Talep tahmini ve doğruluğunun bir işletmenin başarısına ve müşteri memnuniyetine doğrudan etkisi bulunmaktadır. Düzgün talep yapısına sahip ürünlerin talep tahmini ve planlamasında birçok yöntem başarılı sonuçlar verirken çoğu zaman diliminde sıfır talep gören aralıklı talep yapısına sahip ürünlerin talep tahmininde başarılı olamamaktadır. Talep büyüklüğünün ve şeklinin değişkenliği bu ürünler için talep tahmini ve planlamanın yapılmasını zorlaştırmaktadır. Bu çalışmasında, aralıklı talep yapısına sahip ürünlerin talep tahminini için Croston yöntemi ve bir yapay sinir ağı modeli olan Çok Katmanlı Algılayıcılar incelenmiştir. Bu yöntemler e-ticaret sektöründe faaliyet gösteren bir işletmenin satış yaptığı bir kategorideki aralıklı talep yapısına sahip ürünlerinin talep tahmini için kullanılmıştır. Daha sonra her bir yöntemin performansı uygun ölçütler kullanılarak ölçülmüştür

Anahtar Kelimeler

Aralıklı talep, çok katmanlı algılayıcılar, yapay sinir ağları

Kaynakça

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