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Technical Note—Risk Aversion in Stochastic Programming with Recourse

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  • David P. Rutenberg

    (Carnegie-Mellon University, Pittsburgh, Pennsylvania)

Abstract

In stochastic programming with recourse the objective is to maximize the expected net payoff. This assumes implicitly no aversion to risk. With risk aversion, the objective becomes to maximize the expected (concave) utility of the net payoffs. Because of the special structure of the problem with risk aversion, a number of computational short cuts are possible in the mathematical program that results. All the second-stage problems can be solved as linear programs. Unfortunately, whether with or without risk aversion, it is necessary to solve the first-stage problem as a nonlinear program. This note shows that the latest representation of the gradient is but a simple modification of the latest representation of the linear objective function without risk aversion.

Suggested Citation

  • David P. Rutenberg, 1973. "Technical Note—Risk Aversion in Stochastic Programming with Recourse," Operations Research, INFORMS, vol. 21(1), pages 377-380, February.
    • Handle: RePEc:inm:oropre:v:21:y:1973:i:1:p:377-380
    DOI: 10.1287/opre.21.1.377
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    Cited by:

    1. Dimitris Bertsimas & Xuan Vinh Doan & Karthik Natarajan & Chung-Piaw Teo, 2010. "Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 580-602, August.

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