國立虎尾科技大學 |

Solving Network Design Problems via Decomposition, Aggregation and Approximation

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Solving Network Design Problems via Decomposition, Aggregation and Approximation / by Andreas Bärmann.
作者:	Bärmann, Andreas.
面頁冊數:	XV, 203 p. 32 illus., 28 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical optimization. -
電子資源:	https://doi.org/10.1007/978-3-658-13913-1
ISBN:	9783658139131

Solving Network Design Problems via Decomposition, Aggregation and Approximation
Bärmann, Andreas.

Solving Network Design Problems via Decomposition, Aggregation and Approximation [electronic resource] /by Andreas Bärmann. - 1st ed. 2016. - XV, 203 p. 32 illus., 28 illus. in color.online resource.

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

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 < 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.

ISBN: 9783658139131

Standard No.: 10.1007/978-3-658-13913-1doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5-402.6

Dewey Class. No.: 519.6

Solving Network Design Problems via Decomposition, Aggregation and Approximation
LDR:03072nam a22003855i 4500 001 974885
003 DE-He213
005 20200702141106.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783658139131 $9 978-3-658-13913-1
024 7 $a 10.1007/978-3-658-13913-1 $2 doi
035 $a 978-3-658-13913-1
050 4 $a QA402.5-402.6
072 7 $a PBU $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBU $2 thema
082 0 4 $a 519.6 $2 23
100 1 $a Bärmann, Andreas. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1269546
245 1 0 $a Solving Network Design Problems via Decomposition, Aggregation and Approximation $h [electronic resource] / $c by Andreas Bärmann.
250 $a 1st ed. 2016.
264 1 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer Spektrum, $c 2016.
300 $a XV, 203 p. 32 illus., 28 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Decomposition for Multi-Period Network Design -- Solving Network Design Problems via Aggregation -- Approximate Second-Order Cone Robust Optimization.
520 $a 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 < 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.
650 0 $a Mathematical optimization. $3 527675
650 0 $a Operations research. $3 573517
650 0 $a Decision making. $3 528319
650 0 $a Business logistics. $3 562973
650 1 4 $a Optimization. $3 669174
650 2 4 $a Operations Research/Decision Theory. $3 669176
650 2 4 $a Logistics. $3 643936
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783658139124
776 0 8 $i Printed edition: $z 9783658139148
856 4 0 $u https://doi.org/10.1007/978-3-658-13913-1
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)