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E-book
Author Küchler, Christian

Title Stability, approximation, and decomposition in two- and multistage stochastic programming / Christian Küchler
Edition 1. Aufl
Published Wiesbaden : Vieweg + Teubner, 2009

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Description 1 online resource (x, 168 pages) : illustrations
Series Vieweg + Teubner research : Stochastic programming
Vieweg+Teubner research. Stochastic programming.
Contents Preface; Contents; List of Figures; List of Tables; Index of Notation; Chapter 1 Introduction; 1.1 Stochastic Programming Models; 1.2 Approximations, Stability, and Decomposition; 1.3 Contributions; Chapter 2 Stability of Multistage Stochastic Programs; 2.1 Problem Formulation; 2.2 Continuity of the Recourse Function; 2.3 Approximations; 2.4 Calm Decisions; 2.5 Stability; Chapter 3 Recombining Trees for Multistage Stochastic Programs; 3.1 Problem Formulation and Decomposition; 3.2 An Enhanced Nested Benders Decomposition; 3.3 Construction of Recombining Trees; 3.4 Case Study
Summary Stochastic programming provides a framework for modelling, analyzing, and solving optimization problems with some parameters being not known up to a probability distribution. Such problems arise in a variety of applications, such as inventory control, financial planning and portfolio optimization, airline revenue management, scheduling and operation of power systems, and supply chain management. Christian Küchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees. The approach combines the concept of cut sharing with a specific aggregation procedure and prevents an exponentially growing number of subproblem evaluations. Convergence results and numerical properties are discussed
Notes Diss.: Berlin, Humboldt-University, 2009
Bibliography Includes bibliographical references (pages 159-168)
Notes Print version record
Subject Stochastic programming.
Mathematical optimization.
Mathematical optimization
Stochastic programming
Genre/Form dissertations.
Academic theses
Academic theses.
Thèses et écrits académiques.
Form Electronic book
ISBN 9783834893994
3834893994
3834809217
9783834809216