Solving Network Design Problems via Decomposition, Aggregation and Approximation - Softcover

Bärmann, Andreas

Softcover

ISBN 10: 3658139129 ISBN 13: 9783658139124

Publisher: Springer Spektrum, 2016

Synopsis

Andreas Bärmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time.

About this title

About the Author

Dr. Andreas Bärmann is currently working as a postdoctoral researcher at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) at the chair of Economics, Discrete Optimization and Mathematics. His research is focussed on mathematical optimization, especially the optimization of logistic processes.

From the Back Cover

Andreas Bärmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time.

Contents

• Decomposition for Multi-Period Network Design
• Solving Network Design Problems via Aggregation
• Approximate Second-Order Cone Robust Optimization

Target Groups

• Researchers, teachers and students in mathematical optimization and operations research
• Network planners in the field of logistics and beyond

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About the Author

Dr. Andreas Bärmann is currently working as a postdoctoral researcher at the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) at the chair of Economics, Discrete Optimization and Mathematics. His research is focussed on mathematical optimization, especially the optimization of logistic processes.

Edition details

• Publisher: Springer Spektrum
• Publication date: 2016
• Language: English
• ISBN 10: 3658139129
• ISBN 13: 9783658139124
• Binding: Paperback
• Edition number: 1
• Number of pages: 218