Solving Network Design Problems via Decomposition, Aggregation and Approximation

Andreas Bärmann

ISBN 10: 3658139129 / ISBN 13: 9783658139124

Published by Springer Gabler Jun 2016, 2016

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch.

Seller Inventory # 9783658139124

Bibliographic Details

• Title: Solving Network Design Problems via Decomposition, Aggregation and Approximation
• Publisher: Springer Gabler Jun 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3658139129
• ISBN 13: 9783658139124
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 240W x 168H x 13D millimeters 240 millimeters width by 168 millimeters height by 13 millimeters depth
• Weight: 378 grams

About this title

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 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.