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Solving Network Design Problems via Decomposition, Aggregation and Approximation

Autor Andreas Bärmann
en Limba Engleză Paperback – 10 iun 2016
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.
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Specificații

ISBN-13: 9783658139124
ISBN-10: 3658139129
Pagini: 203
Ilustrații: XV, 203 p. 32 illus., 28 illus. in color.
Dimensiuni: 168 x 240 x 12 mm
Greutate: 0.36 kg
Ediția:1st ed. 2016
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Locul publicării:Wiesbaden, Germany

Cuprins

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

Notă biografică

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.

Textul de pe ultima copertă

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.

Caracteristici

A Study in the Field of Mathematics Includes supplementary material: sn.pub/extras