Stochastic Multi-Stage Optimization At the Crossroads between Discre
The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need
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Pierre Carpentier Jean-Philippe Chancelier Guy Cohen Michel De Lara
Stochastic Multi-Stage Optimization At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming
Probability Theory and Stochastic Modelling Volume 75
Editors-in-Chief Søren Asmussen, Aarhus, Denmark Peter W. Glynn, Stanford, CA, USA Thomas G. Kurtz, Madison, WI, USA Yves Le Jan, Orsay, France Advisory Board Joe Gani, Canberra, ACT, Australia Martin Hairer, Coventry, UK Peter Jagers, Gothenburg, Sweden Ioannis Karatzas, New York, NY, USA Frank P. Kelly, Cambridge, UK Andreas E. Kyprianou, Bath, UK Bernt Øksendal, Oslo, Norway George Papanicolaou, Stanford, CA, USA Etienne Pardoux, Marseille, France Edwin Perkins, Vancouver, BC, Canada Halil Mete Soner, Zürich, Switzerland
The Probability Theory and Stochastic Modelling series is a merger and continuation of Springer’s two well established series Stochastic Modelling and Applied Probability and Probability and Its Applications series. It publishes research monographs that make a significant contribution to probability theory or an applications domain in which advanced probability methods are fundamental. Books in this series are expected to follow rigorous mathematical standards, while also displaying the expository quality necessary to make them useful and accessible to advanced students as well as researchers. The series covers all aspects of modern probability theory including • • • • • •
Gaussian processes Markov processes Random Fields, point processes and random sets Random matrices Statistical mechanics and random media Stochastic analysis
as well as applications that include (but are not restricted to): • Branching processes and other models of population growth • Communications and processing networks • Computational methods in probability and stochastic processes, including simulation • Genetics and other stochastic models in biology and the life sciences • Information theory, signal processing, and image synthesis • Mathematical economics and finance • Statistical methods (e.g. empirical processes, MCMC) • Statistics for stochastic processes • Stochastic control • Stochastic models in operations research and stochastic optimization • Stochastic models in the physical sciences
More information about this series at http://www.springer.com/series/13205
Pierre Carpentier Jean-Philippe Chancelier Guy Cohen Michel De Lara •
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Stochastic Multi-Stage Optimization At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming
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Pierre Carpentier ENSTA ParisTech Palaiseau France Jean-Philippe Chancelier CERMICS École Nationale des Ponts et Chaussées ParisTech Marne la Vallée France
Guy Cohen CERMICS École Nationale des Ponts et Chaussées ParisTech Marne la Vallée France Michel De Lara CERMICS École Nationale des Ponts et Chaussées ParisTech Marne la Vallée France
ISSN 2199-3130 ISSN 2199-3149 (electronic) Probability Theory and Stochastic Modelling ISBN 978-3-319-18137-0 ISBN 978-3-319-18138-7 (eBook) DOI 10.1007/978-3-319-18138-7 Li
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