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Repairing Misbehaving Mathematical Programming Models: Concepts and a GAMS-Based Approach

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  • Bruce A. McCarl

    (Department of Agricultural Economics, Texas A&M University, College Station, Texas 77843-2124)

Abstract

Mathematical-programming formulations can yield faulty answers. Models can be unbounded, infeasible, or optimal with unrealistic answers. I develop techniques for screening mathematical-programming formulations for structural problems pre- and postsolution. The presolution approaches identify problems within single variables and constraints. The postsolution techniques may require model augmentation and rely on theory-based examination of primal and dual solutions. I demonstrate these approaches in the context of linear programming and have computerized them in association with GAMS. They are freely distributed through a web page.

Suggested Citation

  • Bruce A. McCarl, 1998. "Repairing Misbehaving Mathematical Programming Models: Concepts and a GAMS-Based Approach," Interfaces, INFORMS, vol. 28(5), pages 124-138, October.
    • Handle: RePEc:inm:orinte:v:28:y:1998:i:5:p:124-138
    DOI: 10.1287/inte.28.5.124
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    References listed on IDEAS

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    1. Harvey J. Greenberg, 1994. "How to Analyze the Results of Linear Programs—Part 4: Forcing Substructures," Interfaces, INFORMS, vol. 24(1), pages 121-130, February.
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    Cited by:

    1. Frederic H. Murphy, 2005. "ASP, The Art and Science of Practice: Elements of a Theory of the Practice of Operations Research: Expertise in Practice," Interfaces, INFORMS, vol. 35(4), pages 313-322, August.

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    Keywords

    linear programming; application;

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