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Sensitivity Analysis and Uncertainty in Linear Programming

Author

Listed:
  • Julia L. Higle

    () (Department of Systems and Industrial Engineering, University of Arizona, Tucson, Arizona 85721)

  • Stein W. Wallace

    () (Molde University College, PO Box 2110, N-6402 Molde, Norway)

Abstract

Linear programming (LP) is one of the great successes to emerge from operations research and management science. It is well developed and widely used. LP problems in practice are often based on numerical data that represent rough approximations of quantities that are inherently difficult to estimate. Because of this, most LP-based studies include a postoptimality investigation of how a change in the data changes the solution. Researchers routinely undertake this type of sensitivity analysis (SA), and most commercial packages for solving linear programs include the results of such an analysis as part of the standard output report. SA has shortcomings that run contrary to conventional wisdom. Alternate models address these shortcomings.

Suggested Citation

  • Julia L. Higle & Stein W. Wallace, 2003. "Sensitivity Analysis and Uncertainty in Linear Programming," Interfaces, INFORMS, vol. 33(4), pages 53-60, August.
  • Handle: RePEc:inm:orinte:v:33:y:2003:i:4:p:53-60
    as

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    File URL: http://dx.doi.org/10.1287/inte.33.4.53.16370
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. E. Borgonovo & L. Peccati, 2011. "Managerial insights from service industry models: a new scenario decomposition method," Annals of Operations Research, Springer, vol. 185(1), pages 161-179, May.
    2. Xin Wang & Stein W. Wallace, 2016. "Stochastic scheduled service network design in the presence of a spot market for excess capacity," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(4), pages 393-413, December.
    3. Rolf Golombek & Kjell Arne Brekke & Michal Kaut & Sverre A.C. Kittelsen & Stein W. Wallace, 2016. "Stochastic equilibrium modeling: The Impact of Uncertainty on the European Energy Market," EcoMod2016 9201, EcoMod.
    4. Z.N. Chen & C.K.M. Lee & W.H. Ip & G.T.S. Ho, 2012. "Design and evaluation of an integrated inventory and transportation system," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(4), pages 491-507, January.
    5. Francesca Maggioni & Stein Wallace, 2012. "Analyzing the quality of the expected value solution in stochastic programming," Annals of Operations Research, Springer, vol. 200(1), pages 37-54, November.
    6. Arnt-Gunnar Lium & Teodor Gabriel Crainic & Stein W. Wallace, 2009. "A Study of Demand Stochasticity in Service Network Design," Transportation Science, INFORMS, vol. 43(2), pages 144-157, May.
    7. Stein Wallace, 2010. "Stochastic programming and the option of doing it differently," Annals of Operations Research, Springer, vol. 177(1), pages 3-8, June.
    8. repec:spr:joptap:v:155:y:2012:i:3:d:10.1007_s10957-012-0089-3 is not listed on IDEAS
    9. repec:eee:energy:v:134:y:2017:i:c:p:984-990 is not listed on IDEAS

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