Authors: Dejan Mircetic, Svetlana Nikolicic, Marinko Maslaric, Nebojsa Ralevic and Borna Debelic

 

Journal Title: Open Engineering
 
ISSN: 2391-5439 (Online)
 
Publisher: De Gruyter Open
 
Abstract
 
Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers.
 
In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.
 
©2016 D. Mircetic et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

Illustration Photo: Miller Brewery Factory (Credits: Alan English CPA / Flickr CC BY-NC 2.0)

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