Abstract
The authors introduce mathematical programming formulations as new approaches to solve the classification problem in discriminant analysis. These formulations have recently emerged as powerful alternatives to the existing methods of maximizing correct classification of entities into groups. The research literature on mathematical programming formulations is reviewed and summarized. An illustration using a real-world classification problem is provided. issues relevant to potential users of these formulations as well as fruitful future research avenues are discussed.
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