This paper describes how to design rules to support linear programming analysis in three functional categories: postoptimal sensitivity, debugging, and model management. The ANALYZE system is used to illustrate the behavior of the rules with a variety of examples. Postoptimal sensitivity analysis answers not only the paradigmWhat if …? question, but also the more frequently askedWhy …? question. The latter is static, asking why some solution value is what it is, or why it is not something else. The former is dynamic, asking how the solution changes if some element is changed. Debugging can mean a variety of things; here the focus is on diagnosing an infeasible instance. Model management includes documentation, verification, and validation. Rules are illustrated to provide support in each of these related functions, including some that require reasoning about the linear program's structure. Another model management function is to conduct a periodic review, with one of the goals being to simplify the model, if possible. The last illustration is how to test new rule files, where there is a variety of ways to communicate a result to someone who is not expert in linear programming.
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Greenberg, H.J. The ANALYZE rulebase for supporting LP analysis. Ann Oper Res 65, 91–126 (1996). https://doi.org/10.1007/BF02187328
- Linear programming
- large-scale systems
- computer-assisted analysis
- computational economics
- sensitivity analysis
- model management