MCDMRelative error metric
Mean Absolute Percentage Error (MAPE)
Mean Absolute Percentage Error measures prediction accuracy as a percentage relative to actual values, expressing errors in units that are scale-independent and interpretable across datasets. Formalized by J. Scott Armstrong in 1985, MAPE is widely used in forecasting, supply chain, and business analytics where results must be communicated as percentage accuracy.
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Sources
- Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010
- Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. DOI: 10.1016/j.ijforecast.2006.03.001 ↗
- Kim, S., & Kim, H. (2016). A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting, 32(3), 669-679. DOI: 10.1016/j.ijforecast.2015.12.003 ↗