Representation Schemes for Linear Programming Models

Because of the difficulties often experienced in formulating and understanding large-scale models, much current research is directed towards developing systems to support the construction and understanding of management science models. This paper discusses eight different methods for representing linear programming models during the formulation phase. The approaches discussed are matrix generators, block-schematic and algebraic languages, three different kinds of graphical schemes, a database-oriented approach and Structured Modeling. While these eight approaches do not cover the entire spectrum of possible representation schemes, they are representative of past and current approaches to developing interfaces for large-scale linear programming systems. The different model representation schemes are compared using a common example and the transformations that allow one to change from one representation to another are discussed.

• 저널Management Science · 38(7) · 964–991
• 토픽Complex Systems and Decision Making · Management Science and Operations Research
• DOI10.1287/mnsc.38.7.964
• 저자Frederic H. Murphy, Edward A. Stohr, Ajay Asthana