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Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integration corresponding to data definition and manipulation, respectively. A model manipulation language based on structured modeling and communicating structured models is suggested which incorporates schema and process integration. The use of object-oriented concepts for designing and implementing integrated modeling environments is discussed. Model integration is projected as the springboard for building a theory of models equivalent in power to relational theory in the database community.

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 existmg operations research, database management, and artificial intelligence techniques. By incorporatmg 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 knowledgebased MMS are discussed and a prototype system for mathematical programming, the Generalized experimentalMath Programming system (GXMP), is described. An algebraic language developed for use in GXMP is described in (detail.

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