Stochastic Optimization Methods

by Kurt Marti

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Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation...Read more
  • ISBN10 354080241X
  • ISBN13 9783540802419
  • Publish Date 10 September 2008 (first published 8 October 2004)
  • Publish Status Withdrawn
  • Out of Print 18 October 2014
  • Publish Country US
  • Imprint Springer
  • Format Paperback (US Trade)
  • Pages 332
  • Language English