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Das Buch gibt eine Einfuhrung in das neue Gebiet der Analyse und Optimierung von Tragwerken unter stochastischer Unsicherheit. Es werden die Grundlagen ausfuhrlich dargestellt und zum Teil von unterschiedlichen Standpunkten aus beleuchtet.

In Teil I wird die lineare Theorie der Stabtragwerke als Grundlage fur die FEM entwickelt. Vorausgesetzt werden dabei nur wenige Kenntnisse aus der Technischen Mechanik und der Ingenieurmathematik, insbesondere eine gewisse Vertrautheit mit der Matrizenrechnung.

In Teil II wird dargestellt, wie sich die...

This book examines optimization problems that in practice involve random model parameters. It outlines the computation of robust optimal solutions, i.e., optimal solutions that are insensitive to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into corresponding deterministic problems.

Due to the probabilities and expectations involved, the book also shows how to apply...

This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems.

Due to the probabilities and expectations involved, the book also shows...

Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insenistive with respect to random parameter variations, appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Several...

Support for addressing the on-going global changes needs solutions for new scientific problems which in turn require new concepts and tools. A key issue concerns a vast variety of irreducible uncertainties, including extreme events of high multidimensional consequences, e.g., the climate change. The dilemma is concerned with enormous costs versus massive uncertainties of extreme impacts. Traditional scientific approaches rely on real observations and experiments. Yet no sufficient observations exist for new problems, and "pure" experiments, and learning by doing may be expensive,...