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035   $a(DE-He213)978-3-540-45586-8
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100   $a20121227d2001      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aComputational Combinatorial Optimization$b[electronic resource] $eOptimal or Provably Near-Optimal Solutions /$fedited by Michael Jünger, Denis Naddef
205   $a1st ed. 2001.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2001.
215   $a1 online resource (X, 310 p.) 
225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v2241
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-540-42877-1 
320   $aIncludes bibliographical references at the end of each chapters and index.
327   $aGeneral Mixed Integer Programming: Computational Issues for Branch-and-Cut Algorithms -- Projection and Lifting in Combinatorial Optimization -- Mathematical Programming Models and Formulations for Deterministic Production Planning Problems -- Lagrangian Relaxation -- Branch-and-Cut Algorithms for Combinatorial Optimization and Their Implementation in ABACUS -- Branch, Cut, and Price: Sequential and Parallel -- TSP Cuts Which Do Not Conform to the Template Paradigm.
330   $aThis tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.
410  0$aLecture Notes in Computer Science,$x0302-9743 ;$v2241
606   $aMathematical optimization
606   $aComputer science?Mathematics
606   $aAlgorithms
606   $aInformation technology
606   $aBusiness?Data processing
606   $aData structures (Computer science)
606   $aCombinatorics
606   $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008
606   $aDiscrete Mathematics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17028
606   $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021
606   $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000
606   $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017
606   $aCombinatorics$3https://scigraph.springernature.com/ontologies/product-market-codes/M29010
615  0$aMathematical optimization.
615  0$aComputer science?Mathematics.
615  0$aAlgorithms.
615  0$aInformation technology.
615  0$aBusiness?Data processing.
615  0$aData structures (Computer science).
615  0$aCombinatorics.
615 14$aOptimization.
615 24$aDiscrete Mathematics in Computer Science.
615 24$aAlgorithm Analysis and Problem Complexity.
615 24$aIT in Business.
615 24$aData Structures.
615 24$aCombinatorics.
676   $a519.7
702   $aJünger$b Michael$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aNaddef$b Denis$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996465664603316
996   $aComputational combinatorial optimization$9972204
997   $aUNISA