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A practical approach to sensitivity analysis in linear programming under degeneracy for management decision making

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  • Koltai, Tamás
  • Tatay, Viola

Abstract

Linear programming (LP) is a widely used tool in management decision making. Theoretically, sensitivity analysis of LP problems provides useful information for the decision maker. In practice, however, most LP software provides misleading sensitivity information if the optimal solution is degenerate. The paper shows how sensitivity analysis of LP problems can be done correctly when the optimal solution is degenerate. A production planning example is presented to illustrate the incorrect sensitivity analysis results automatically provided by most LP solvers. The general characteristics of the misleading results and the possible effects of this incorrect information on management decisions are also discussed.

Suggested Citation

  • Koltai, Tamás & Tatay, Viola, 2011. "A practical approach to sensitivity analysis in linear programming under degeneracy for management decision making," International Journal of Production Economics, Elsevier, vol. 131(1), pages 392-398, May.
  • Handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:392-398
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    2. Koltai, Tamas & Terlaky, Tamas, 2000. "The difference between the managerial and mathematical interpretation of sensitivity analysis results in linear programming," International Journal of Production Economics, Elsevier, vol. 65(3), pages 257-274, May.
    3. Hadigheh, Alireza Ghaffari & Terlaky, Tamas, 2006. "Sensitivity analysis in linear optimization: Invariant support set intervals," European Journal of Operational Research, Elsevier, vol. 169(3), pages 1158-1175, March.
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    Cited by:

    1. Silvia Araújo dos Reis & José Eugenio Leal & Antônio Márcio Tavares Thomé, 2023. "A Two-Stage Stochastic Linear Programming Model for Tactical Planning in the Soybean Supply Chain," Logistics, MDPI, vol. 7(3), pages 1-26, August.
    2. Borgonovo, Emanuele & Buzzard, Gregery T. & Wendell, Richard E., 2018. "A global tolerance approach to sensitivity analysis in linear programming," European Journal of Operational Research, Elsevier, vol. 267(1), pages 321-337.

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