Conditioning of convex piecewise linear stochastic programs

Alexander Shapiro, Tito Homem-De-Mello, Joocheol Kim

Research output: Contribution to journalArticlepeer-review

49 Citations (Scopus)


In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal solution of such a problem we associate a condition number which characterizes well or ill conditioning of the problem. Using theory of Large Deviations we show that the sample size needed to calculate the optimal solution of such problem with a given probability is approximately proportional to the condition number.

Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalMathematical Programming, Series B
Issue number1
Publication statusPublished - 2002 Dec

All Science Journal Classification (ASJC) codes

  • Software
  • Mathematics(all)


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