Classifying and controlling errors in forecasting using multiple criteria goal programming

This paper is concerned with the use of multiple criteria goal programming as a method of combining forecasts. The forecasts to be combined can come from a variety of forecasting techniques as well as from a variety of forecasting lead times. The model provided in this paper provides a generalization of previous work in the use of mathematical programming in combining forecasts. The generalizations are of two types; an error classification scheme such that the decision-maker can prioritize error types, and an error tolerance zone such that errors that fall within the prescribed tolerance zone may have no impact on the final forecasting model. The resultant structure affords considerably more flexibility in developing a model that matches the priorities deemed important to the decision maker given the forecasting information available.