ARIMA is usually not used in supply chain for various reasons, including the complications in order definition and speed of estimation of its parameters. We propose an approach that overcomes the main limitations of ARIMA and allows using it for supply chain forecasting.
Development of forecasting algorithms which will run quickly in practice.
This research has led to the implementation of new features in the commercial Smoothie forecasting package.
| Status | Active |
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| Effective start/end date | 13/07/16 → … |
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