Articles liés à Risk Management in Stochastic Integer Programming:...

Risk Management in Stochastic Integer Programming: With Application to Dispersed Power Generation - Couverture souple

Neise, Frederike

 
9783834805478: Risk Management in Stochastic Integer Programming: With Application to Dispersed Power Generation
Couverture souple
ISBN 10 : 3834805475 ISBN 13 : 9783834805478
Editeur : Vieweg+Teubner Verlag, 2008

Synopsis

The author presents two concepts to handle the classic linear mixed-integer two-stage stochastic optimization problem. She describes mean-risk modeling and stochastic programming with first order dominance constraints. Both approaches are applied to optimize the operation of a dispersed generation system.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Dr. Frederike Neise gained a PhD in Mathematics from the University of Duisburg-Essen studying two-stage stochastic programming and its application to the optimal management of dispersed generation systems. She currently works as a gas market analyst with E.ON Ruhrgas AG.

À propos de la quatrième de couverture

Two-stage stochastic optimization is a useful tool for making optimal decisions under uncertainty. Frederike Neise describes two concepts to handle the classic linear mixed-integer two-stage stochastic optimization problem: The well-known mean-risk modeling, which aims at finding a best solution in terms of expected costs and risk measures, and stochastic programming with first order dominance constraints that heads towards a decision dominating a given cost benchmark and optimizing an additional objective. For this new class of stochastic optimization problems results on structure and stability are proven. Moreover, the author develops equivalent deterministic formulations of the problem, which are efficiently solved by the presented dual decomposition method based on Lagrangian relaxation and branch-and-bound techniques. Finally, both approaches mean-risk optimization and dominance constrained programming are applied to find an optimal operation schedule for a dispersed generation system, a problem from energy industry that is substantially influenced by uncertainty.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Vieweg+Teubner Verlag
Date d'édition
2008
Langue
anglais
ISBN 10 
3834805475
ISBN 13 
9783834805478
Reliure
Broché
Nombre de pages
116
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