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Aspects of optimization with stochastic dominance

Author

Listed:
  • William B. Haskell

    (National University of Singapore)

  • J. George Shanthikumar

    (Purdue University)

  • Z. Max Shen

    (University of California Berkeley)

Abstract

We consider stochastic optimization problems with integral stochastic order constraints. This problem class is characterized by an infinite number of constraints indexed by a function space of increasing concave utility functions. We are interested in effective numerical methods and a Lagrangian duality theory. First, we show how sample average approximation and linear programming can be combined to provide a computational scheme for this problem class. Then, we compute the Lagrangian dual problem to gain more insight into this problem class.

Suggested Citation

  • William B. Haskell & J. George Shanthikumar & Z. Max Shen, 2017. "Aspects of optimization with stochastic dominance," Annals of Operations Research, Springer, vol. 253(1), pages 247-273, June.
    • Handle: RePEc:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2299-9
    DOI: 10.1007/s10479-016-2299-9
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    References listed on IDEAS

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