Forecasting and Queuing Theory
Understanding how demand, flow, and capacity change over time is essential when systems must perform under uncertainty. Forecasting and queuing theory offer ways to anticipate future patterns and examine how delays and congestion arise, helping make sense of time-dependent behaviour in complex environments.
Technique Overview
Forecasting and Queuing Theory Definition
Forecasting and queuing theory are statistical methods used to understand and manage systems that change over time. Forecasting focuses on estimating future values, such as demand or workload, based on historical patterns, while queuing theory examines how capacity, arrival rates, and service processes influence waiting times and congestion. Used together, they support analysis of how anticipated demand interacts with system capacity to affect performance and delay (Hyndman and Athanasopoulos, 2018; Hillier, 2005; Little, 1961).
Forecasting and Queuing Theory Description *
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Business Evidence
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Business Application
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Further Reading
Forecasting and Queuing Theory web and print resources *
Forecasting and Queuing Theory references (4 of up to 20) *
- Hyndman, R.J. and Athanasopoulos, G., 2018. Forecasting: principles and practice. OTexts.
- Box, G.E., Jenkins, G.M., Reinsel, G.C. and Ljung, G.M., 2015. Time series analysis: forecasting and control. John Wiley & Sons.
- Makridakis, S., Spiliotis, E. and Assimakopoulos, V. (2018). Statistical and Machine Learning forecasting methods: Concerns and ways forward. PLOS ONE, 13(3), p.e0194889. doi:https://doi.org/10.1371/journal.pone.0194889.
- Hyndman, R.J. and Koehler, A.B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), pp.679–688. doi:https://doi.org/10.1016/j.ijforecast.2006.03.001.
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