Volume List  / Volume 10 (3)



DOI: 10.7708/ijtte.2020.10(3).01

10 / 3 / 266 - 277 Pages


Pavle Bugarčić - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia -

Valentina Radojičić - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia -


A company can predict satisfactory staffing and scheduling levels, improve service requirements, meet customer satisfaction by forecasting the real number of incoming calls. Accurate forecast of customer demand is crucial for the staffing algorithm of a telephone Call Center. There is a problem of scheduling and re-scheduling the available pool of agents based on updated forecasts, typically made weeks or months in advance. Here, we selected some forecasting methods that can generate both time-varying and stochastic day-to-day demand. This paper proposes three different methods in detail: the Moving Averages method, Simple Exponential Smoothing method, and Additive Holt-Winters method. We presented the forecasting results obtained from an empirical study analyzing real Call Center data by months. Finally, each of these methods was tested and the comparison results are given.

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This paper has been partially supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia project under No. 32025.


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