Determining the Optimal Values of Exponential Smoothing Constants--Does Solver Really Work?

Authors

Handanhal Ravinder, Montclair State UniversityFollow

Document Type

Article

Publication Date

2013

Journal / Book Title

American Journal of Business Education

Abstract

A key issue in exponential smoothing is the choice of the values of the smoothing constants used. One approach that is becoming increasingly popular in introductory management science and operations management textbooks is the use of Solver, an Excel-based non-linear optimizer, to identify values of the smoothing constants that minimize a measure of forecast error like Mean Absolute Deviation (MAD) or Mean Squared Error (MSE). We point out some difficulties with this approach and suggest an easy fix. We examine the impact of initial forecasts on the smoothing constants and the idea of optimizing the initial forecast along with the smoothing constants. We make recommendations on the use of Solver in the context of the teaching of forecasting and suggest that there is a better method than Solver to identify the appropriate smoothing constants.

Comments

ERIC Number: EJ1054363

Journal ISSN / Book ISBN

1942-2504

MSU Digital Commons Citation

Ravinder, Handanhal, "Determining the Optimal Values of Exponential Smoothing Constants--Does Solver Really Work?" (2013). Department of Management Faculty Scholarship and Creative Works. 1.
https://digitalcommons.montclair.edu/management-facpubs/1

Published Citation

Ravinder, Handanhal V. 2013. “Determining the Optimal Values of Exponential Smoothing Constants--Does Solver Really Work?” American Journal of Business Education 6 (3): 347–60.