Inverse cutting plane methods for optimization problems with second-order stochastic dominance constraints

Darinka Dentcheva, Andrzej Ruszczyński

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

We propose new cutting plane methods for solving optimization problems with second-order stochastic dominance constraints. The methods are based on the inverse formulation of stochastic dominance constraints using Lorenz functions. Convergence of the methods is proved for general probability distributions. For general discrete distributions convergence is finite. Numerical experiments on a portfolio problem confirm efficiency of the methods.

Original languageEnglish
Pages (from-to)323-338
Number of pages16
JournalOptimization
Volume59
Issue number3
DOIs
StatePublished - Apr 2010

Keywords

  • Conditional value-at-risk
  • Cutting plane methods
  • Lorenz curve
  • Portfolio optimization
  • Stochastic dominance

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