Using Artificial Intelligence to Enhance Model Analysis

  • Ramesh Sharda
  • David M. Steiger
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 4)


The purpose of mathematical modeling is to generate insights into the decision making environment being modeled. Such insights are often generated through the analysis of several, if not many, related model instances. However, little theory and only a few systems have been developed to support this basic goal of modeling. Nonlinear modeling capabilities of neural networks and related methods can be employed to identify patterns within the multiple ‘what-if’ instances.

The purpose of this paper is to describe a prototype, artificial intelligence-based system, named INSIGHT, which analyzes multiple, related model instances to identify key model parameters and develop insights into how these key parameters interact to influence the model solution.


Mixed Integer Linear Programming Model Instance Scenario Manager Global Sensitivity Analysis Auxiliary Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • Ramesh Sharda
    • 1
  • David M. Steiger
    • 2
  1. 1.College of Business AdministrationOklahoma State UniversityStillwaterUSA
  2. 2.School of BusinessUniversity of North Carolina, GreensboroGreensboroUSA

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