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Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition

Author

Listed:
  • Andrew J. Hogan

    (University of Wisconsin---Madison)

  • James G. Morris

    (University of Wisconsin---Madison)

  • Howard E. Thompson

    (University of Wisconsin---Madison)

Abstract

Some important conceptual problems concerning the application of chance constrained programming (CCP) to risky practical decision problems are discussed by comparing CCP to stochastic programming with recourse (SPR). We expand on Garstka's distinction between mathematical equivalence and economic equivalence showing that much of practical usefulness is lost in the transition between SPR and CCP. By examining the literature on CCP applications we conclude that there is little evidence that CCP is used with the care that is necessary. Finally we conclude that CCP is seriously deficient as a modeling technique and of limited value as a computational device.

Suggested Citation

  • Andrew J. Hogan & James G. Morris & Howard E. Thompson, 1981. "Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition," Management Science, INFORMS, vol. 27(6), pages 698-716, June.
    • Handle: RePEc:inm:ormnsc:v:27:y:1981:i:6:p:698-716
    DOI: 10.1287/mnsc.27.6.698
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    Cited by:

    1. Robert F. Bordley & Stephen M. Pollock, 2009. "A Decision-Analytic Approach to Reliability-Based Design Optimization," Operations Research, INFORMS, vol. 57(5), pages 1262-1270, October.
    2. Colson, Gérard, 1993. "Prenons-nous assez de risque dans les théories du risque?," L'Actualité Economique, Société Canadienne de Science Economique, vol. 69(1), pages 111-141, mars.
    3. L. P. Fatti & A. Mehrez & M. Pachter, 1987. "Bounds and properties of the expected value of sample information for a project‐selection problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(1), pages 141-150, February.
    4. Matthias Schmidt & Alexander Lorenz & Hermann Held & Elmar Kriegler, 2011. "Climate targets under uncertainty: challenges and remedies," Climatic Change, Springer, vol. 104(3), pages 783-791, February.
    5. Zhu, Minkang & Taylor, Daniel B. & Sarin, Subhash C. & Kramer, Randall A., 1994. "Chance Constrained Programming Models For Risk-Based Economic And Policy Analysis Of Soil Conservation," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 23(1), pages 1-8, April.
    6. Mehrez, Abraham, 1997. "The interface between OR/MS and decision theory," European Journal of Operational Research, Elsevier, vol. 99(1), pages 38-47, May.
    7. Mehrez, A. & Yuan, Y. & Gafni, A., 1995. "The search for information -- A patient perspective on multiple opinions," European Journal of Operational Research, Elsevier, vol. 85(2), pages 244-262, September.
    8. McCarl, Bruce A., 1986. "Innovations In Programming Techniques For Risk Analysis," Regional Research Projects > 1986: S-180 Annual Meeting, March 23-26, 1986, Tampa, Florida 271825, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.
    9. Lixia H. Lambert & Eric A. DeVuyst & Burton C. English & Rodney Holcomb, 2021. "Analyzing the Trade-Offs between Meeting Biorefinery Production Capacity and Feedstock Supply Cost: A Chance Constrained Approach," Energies, MDPI, vol. 14(16), pages 1-13, August.
    10. Laslo, Zohar & Gurevich, Gregory & Keren, Baruch, 2009. "Economic distribution of budget among producers for fulfilling orders under delivery chance constraints," International Journal of Production Economics, Elsevier, vol. 122(2), pages 656-662, December.
    11. Abbas Afshar & Fariborz Masoumi & Sam Solis, 2015. "Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2045-2058, April.

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