Abstract
ABSTRACTThis paper presents research on the problem of selecting a proper surrogate for a forecast error cost criterion in the production smoothing problem. Various forecast models estimated future selected demand process values. Resultant error costs were computed and the coincidence of the selection of a forecast model on the basis of least error cost and the various error measures was noted. The error measures used were the mean absolute deviation, average algebraic error(bias), and the mean squared error. Computations necessary to develop the mathematical form of the error cost criterion are presented in an Appendix. Also presented are the penalty costs of using an error measure as a surrogate for an error cost criterion.
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