Description

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.

Stochastic Multi-Stage Optimization: At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming

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Hardback by Pierre Carpentier , Jean-Philippe Chancelier

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The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on... Read more

    Publisher: Springer International Publishing AG
    Publication Date: 19/05/2015
    ISBN13: 9783319181370, 978-3319181370
    ISBN10: 3319181378

    Number of Pages: 362

    Non Fiction , Mathematics & Science , Education

    Description

    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.

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