|edoc-Server der Humboldt-Universität zu Berlin|
Alexander Shapiro, Georgia Institute of Technology|
Joocheol Kim, Georgia Institute of Technology
Tito Homem-de-Mello, The Ohio State University
|Title:||Conditioning of stochastic programs|
|Date of Acceptance:||26.06.2000|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10057688)|
|Keywords (eng):||Monte Carlo simulation, stochastic programming, Large Deviations theory, ill conditioned problems|
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
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|In this paper we consider stochastic programming problems where the objective function is given as an expected value function. With an optimal solution of such a (convex) problem we associate a condition number which characterizes well or ill conditioning of the problem. 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.|
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