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Linearization Method for Solving Equilibrium Programming Problems Read chapter Read first chapter

2000 | OriginalPaper | Chapter

An Ergodic Theorem for Stochastic Programming Problems

Authors : Lisa A. Korf, Roger J-B Wets

Published in: Optimization

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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To justify the use of sampling to solve stochastic programming problems one usually relies on a law of large numbers for random lsc (lower semicontinuous) functions when the samples come from independent, identical experiments. If the samples come from a stationary process, one can appeal to the ergodic theorem proved here. The proof relies on the ‘scalarization’ of random lsc functions.

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Metadata
Title
An Ergodic Theorem for Stochastic Programming Problems
Authors
Lisa A. Korf
Roger J-B Wets
Copyright Year
2000
Publisher
Springer Berlin Heidelberg
Book
Optimization

Print ISBN: 978-3-540-66905-0

Electronic ISBN: 978-3-642-57014-8

Copyright Year: 2000

DOI
https://doi.org/10.1007/978-3-642-57014-8_14

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