This paper investigates some reasoning issues involved in developing an integrated modeling environment called a model management system. A model management system is a computer-based environment designed to support effective development and utilization of quantitative decision models. Since the construction of decision models is a knowledge-intensive process, reasoning plays a critical role. Reasoning is particularly important when automated model integration is needed in a large-scale system. In this case, heuristics are required to reduce the complexity of the process. This paper examines the planning and automated formulation of complex models from smaller building blocks. First, a hierarchy of abstractions that integrates previous contributions in model management is presented. Then, a modeling process is formulated as a planning process by which a set of operators are scheduled to achieve a specific goal. This process involves searches for alternatives that can eliminate the difference between the initial stale and the goal state. Various reasoning strategies and heuristic evaluation Junctions that can be used to improve the efficiency of developing a master plan for model integration are discussed.
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