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 to
tackle uncertainty in applications of optimization. For example the
massive introduction of renewable energies in power systems
challenges traditional ways to manage them. This book lays out
basic and advanced tools to handle and numerically solve such
problems and thereby is building a bridge between Stochastic
Programming and Stochastic Control. It is intended for graduates
readers and scholars in optimization or stochastic control, as well
as engineers with a background in applied mathematics.
General
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