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The Deterministic Equivalents of Chance-Constrained Programming

Author

Listed:
  • Kim, C.S.
  • Schaible, Glenn D.
  • Segarra, Eduardo

Abstract

Three concepts combine to show both the feasibility and desirability of incorporating probability within programming models. First, the reliability of estimates obtained by using Chebyshev's inequality increases as variation measured by the coefficient of variation, declines. Second, the coefficient of variation can be substantially reduced by the use of the mean and variance of a truncated normal distribution. Third, chance-constrained programming can be converted into deterministic equivalent quadratic programming by using the parameters of a truncated normal distribution.

Suggested Citation

  • Kim, C.S. & Schaible, Glenn D. & Segarra, Eduardo, 2. "The Deterministic Equivalents of Chance-Constrained Programming," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, issue 2.
  • Handle: RePEc:ags:uersja:139022
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    File URL: http://purl.umn.edu/139022
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    References listed on IDEAS

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    1. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
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    Cited by:

    1. Matthews, Nicolette & Grove, Bennie, 2015. "Economic-Environmental Trade-offs and the Conservativeness of the Upper Partial Moment," 2015 Conference, August 9-14, 2015, Milan, Italy 212450, International Association of Agricultural Economists.
    2. Athanasios Kampas & Ben White, 2004. "Administrative Costs and Instrument Choice for Stochastic Non-point Source Pollutants," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 27(2), pages 109-133, February.

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