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This paper is concerned with expanding the decision support capabilities of computerized forecasting systems. The expansion allows for the systematic combination of multiple forecasts and the explicit consideration of multiple objectives in the forecast selection process. The methodology used is multiple objective linear programming. Selecting an individual forecast based upon a single objective may not make the best use of available information for a variety of reasons. Combined forecasts may provide a better fit with respect to a single objective than any individual forecast. Even if an individual forecast does provide a good fit with respect to a single objective, a combined forecast may provide a better fit with respect to multiple objectives. An example is used to illustrate the expanded decision support system, its outputs and their properties.