Two-stage stochastic optimization problems with stochastic ordering constraints on the recourse

Darinka Dentcheva, Gabriela Martinez

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

We consider two-stage risk-averse stochastic optimization problems with a stochastic ordering constraint on the recourse function. Two new characterizations of the increasing convex order relation are provided. They are based on conditional expectations and on integrated quantile functions: a counterpart of the Lorenz function. We propose two decomposition methods to solve the problems and prove their convergence. Our methods exploit the decomposition structure of the risk-neutral two-stage problems and construct successive approximations of the stochastic ordering constraints. Numerical results confirm the efficiency of the methods.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalEuropean Journal of Operational Research
Volume219
Issue number1
DOIs
StatePublished - 16 May 2012

Keywords

  • Decomposition methods
  • Increasing convex order
  • Lorenz curve
  • Stochastic dominance
  • Stochastic programming
  • Survival function

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