FORECASTING WATER DEMAND BY USING MONTE CARLO SIMULATION
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Numerous forecasting methods such as qualitative methods, naive approach, time series methods, judgmental methods, artificial intelligence methods, regression analysis, simulation methods and etc. are available for practitioners in the forecasting literature. The main goal of this paper is to present how Monte Carlo Simulation Method is used for forecasting the demand practically and for forecasting the future demands that would help managerial decisions. For this purpose, the data that is comprised of the demand of the dispenser size (19 liters) water bottles of a water company in Bursa was gathered and Monte Carlo Simulation monthly and seasonal forecasts were obtained. Results show that the monthly and seasonal actual values and estimated values were close to each other. By decreasing uncertainty about future through Monte Carlo forecasting method, company managers had the advantage of making healthy future decisions about controlling their inventory, purchasing new equipment, hiring a new worker and other sources.
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Kestirim literaturunde kalitatif yontemler, naive yakla§im, zaman serileri yontemleri, muhakeme yontemleri, yapay zeka yontemleri, regresyon analizi, simulasyon yontemleri ve benzeri yontemler uygulamacilarin kullanimina sunulmu§tur. Bu makalede, asil amag Monte Carlo Benzetim Yonteminin talep kestiriminde uygulamali olarak nasil kullanildiginin gosterilmesi ve yonetici kararlarina yardimci olacak gelecekteki taleplerin kestirilmesidir. Bu amagla, damacana su (19 litre) talebini igeren veriler Bursa'daki bir su §irketinden elde edilmi§tir ve aylik ve mevsimlik Monte Carlo kestirimleri elde edilmi§tir. Sonuglar aylik ve mevsimsel gergek degerler ile tahminlerin birbirine yakin oldugunu gostermektedir. Gelecekteki belirsizligin bilinmesi ile firma yoneticileri envanterlerini kontrol etme, yeni teghizat satin alma, yeni bir elemani i§e alma ve diger kaynaklar hakkinda gelecekte saglikli kararlar alma avantajina sahip olmu§
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