ATM NAKİT İKMAL OPTİMİZASYONUNDA ASİMETRİK DESTEK VEKTÖR REGRESYON TAHMİN MODELİ YAKLAŞIMI

Bankacılık ve finans sektöründe ATM nakit ikmal problemi oldukça önemlidir. Bu problemin çözümü için en düşük tahmin hata oranını veren tahmin modelinin seçilmesinin yanı sıra minimum ikmal maliyetlerini veren optimizasyon modelinin bulunması da büyük bir öneme sahiptir. Bu çalışmada, yeni bir asimetrik tahmin modeli ve bu model ile entegre olarak çalışan, bir başka deyişle, tahmin ve optimizasyondan oluşan, iki aşamalı süreci tek bir aşamaya indiren ve nakit ikmal maliyetlerini minimize eden bir optimizasyon modeli önerilmiştir. Aynı zamanda diğer tahmin modelleri ile maliyet performans karşılaştırılması gerçekleştirilmiştir.

Asymmetric Support Vector Regression Approach in ATM Cash Replenishment Optimization

ATM cash replenishment problem is quite important in banking and finance sector. As well as choosing the forecast model giving the smallest forecast error ratio for the solution of this problem, finding the optimization model giving the minimum replenishment costs has importance. In this study, a new asymmetrical forecast model and an optimization model running integrated with the forecast model, in other words, an optimization model which reduces the two stage forecast and optimization process to a single step is proposed. At the same time, a comparison of costs with the other forecast models is performed.

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