Stochastic Optimization: Numerical Methods and Technical Applications (Lecture Notes in Economics and Mathematical Systems)

ISBN 10: 3540552251 / ISBN 13: 9783540552253

Edité par Springer, 1992

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N° de réf. du vendeur ERICA75835405522515

Détails bibliographiques

• Titre: Stochastic Optimization: Numerical Methods and Technical Applications (Lecture Notes in Economics and Mathematical Systems)
• Éditeur: Springer
• Date de parution: 1992
• Langue: anglais
• ISBN à 10 chiffres: 3540552251
• ISBN à 13 chiffres: 9783540552253
• Reliure: Paperback
• État de l'article: Like New
• Type de livre: book

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Synopsis

This volume includes a selection of papers presented at the GAMM/ IFIP-Workshop on IIStochastic Optimization: Numerical Methods and ll Technical Applications, held at the Federal Armed Forces Univer- sity Munich, May 29-31, 1990. The objective of this meeting was to bring together scientists from Stochastic Programming and from those Engineering areas, where Mathematical Programming models are common tools, as e.g. Optimal structural Design, Power Dispatch, Acid Rain Abatement etc .. Hence, the aim was to discuss the effects of taking into account the in- herent randomness of some data of these problems, i.e. considering Stochastic Programming instead of Mathematical Programming models in order to get solutions being more reliable, but not more expen- sive. An international programme committe2 was formed which included H.A. Eschenauer (Germany) P. Kall (Switzerland) K. Marti (Germany, Chairman) J. Mayer (Hungary) G.I. Schueller (Austria) Although the number of participants had to be small for technical reasons, the area covered by the lectures during the workshop was rather broad. It contains theoretical insight into stochastic pro- gramming problems, new computational approaches, analyses of known solution methods, and applications in such very different technical fields as ecology, energy demands, and optimal reliability of me- chanical structures. In particular, the applied presentation also pointed to several open methodological problems.