This paper examines mathematical programming software in the context of model management and decision support. The concept of a model management system (MMS) is introduced and compared to traditional modeling systems. An MMS is seen as a much more generalized software system that requires the confluence of existing operations research, database management, and artificial intelligence techniques. By incorporating powerful, abstraction-based representation structures, an MMS can support multiple levels of model abstraction, only one of which corresponds to traditional, solution-oriented modeling software. The database structures required to implement a knowledge-based MMS are discussed and a prototype system for mathematical programming, the Generalized eXperimental Math Programming system (GXMP), is described. An algebraic language developed for use in GXMP is described in detail.

This paper examines the concept of a model management system, what its functions are, and how they are to be achieved in a decision support context. The central issue is model representation which involves knowledge representation and knowledge management within a database environment. The model abstraction structure is introduced as a vehicle for model representation which supports both heuristic and deterministic inferencing as well as the conceptual/external schema notion familiar to database management. The model abstraction is seen as a special instance of the frame construct in artificial intelligence. Model management systems are characterized as frame-systems and a database implementation of this approach is described.