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Strong convexity in risk-averse stochastic programs with complete recourse

Author

Listed:
  • Matthias Claus

    (University of Duisburg-Essen)

  • Rüdiger Schultz

    (University of Duisburg-Essen)

  • Kai Spürkel

    (University of Duisburg-Essen)

Abstract

We give sufficient conditions for the expected excess and the mean-upper-semideviation of recourse functions to be strongly convex. This is done in the setting of two-stage stochastic programs with complete linear recourse and random right-hand side. This work extends results on strong convexity of risk-neutral models.

Suggested Citation

  • Matthias Claus & Rüdiger Schultz & Kai Spürkel, 2018. "Strong convexity in risk-averse stochastic programs with complete recourse," Computational Management Science, Springer, vol. 15(3), pages 411-429, October.
    • Handle: RePEc:spr:comgts:v:15:y:2018:i:3:d:10.1007_s10287-018-0331-z
    DOI: 10.1007/s10287-018-0331-z
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    References listed on IDEAS

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    1. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
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