|edoc-Server der Humboldt-Universität zu Berlin|
Adib Bagh, University of California, Davis|
Michael Casey, University of Puget Sound, Tacoma
|Title:||An Ergodic Theorem for Random Lagrangians with an Application to Stochastic Programming|
|Date of Acceptance:||21.07.2003|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10059143)|
|Keywords (eng):||stochastic programming, duality, saddle point, ergodic theory, lagrangian, epi/hyo-convergence|
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|We prove an ergodic theorem showing the almost sure epi/hypo-convergence of a sequence of random lagrangians to a limit lagrangian where the random lagrangians are generated by stationary sampling of a probability measure. We apply this theorem to stochastic programming and demonstrate that the outer set-limit of the sequence of the set of saddle points from the sampled problems is a subset of the set of saddle points of the true problem.|
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