Overview

Optimization problems which arise in practice generally contain several random parameters. In order to get robust optimal solutions with respect to random parameter variations, the available statistical information about the random data should be considered at the planning phase. Thus, the original problem with random coefficients must be replaced by an appropriate deterministic substitute problem. This volume contains the proceedings of the 4th GAMM/IFIP workshop on ""Stochastic Optimization: Numerical Methods and Technical Applications"" held June 27-29th 2000 at the Federal Armed Forces University in Munich. It contains methods for the approximation and numerical solution of deterministic substitute problems, especially the handling of mean value and probability functions as objective and/or constraint functions. The book also includes many concrete applications from engineering and operations research.

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9783540428893

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