LEADER 03753nam  22005535  450 
001 9910254077503321
005 20220407180051.0
010   $a3-658-13913-7
024 7 $a10.1007/978-3-658-13913-1
035   $a(CKB)3710000000721950
035   $a(DE-He213)978-3-658-13913-1
035   $a(MiAaPQ)EBC4538061
035   $a(PPN)194377970
035   $a(EXLCZ)993710000000721950
100   $a20160602d2016      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aSolving network design problems via decomposition, aggregation and approximation /$fby Andreas Bärmann
205   $a1st ed. 2016.
210  1$aWiesbaden :$cSpringer Fachmedien Wiesbaden :$cImprint: Springer Spektrum,$d2016.
215   $a1 online resource (XV, 203 p. 32 illus., 28 illus. in color.)
225 0 $aResearch
311   $a3-658-13912-9 
320   $aIncludes bibliographical references.
327   $aDecomposition for Multi-Period Network Design -- Solving Network Design Problems via Aggregation -- Approximate Second-Order Cone Robust Optimization.
330   $aAndreas 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.
606   $aMathematical optimization
606   $aOperations research
606   $aDecision making
606   $aBusiness logistics
606   $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008
606   $aOperations Research/Decision Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/521000
606   $aLogistics$3https://scigraph.springernature.com/ontologies/product-market-codes/519020
615  0$aMathematical optimization.
615  0$aOperations research.
615  0$aDecision making.
615  0$aBusiness logistics.
615 14$aOptimization.
615 24$aOperations Research/Decision Theory.
615 24$aLogistics.
676   $a519.6
700   $aBärmann$b Andreas$4aut$4http://id.loc.gov/vocabulary/relators/aut$0756079
906   $aBOOK
912   $a9910254077503321
996   $aSolving network design problems via decomposition, aggregation and approximation$91523629
997   $aUNINA