04586nam 22008295 450 99646566460331620200703033443.03-540-45586-810.1007/3-540-45586-8(CKB)1000000000211646(SSID)ssj0000322012(PQKBManifestationID)11277384(PQKBTitleCode)TC0000322012(PQKBWorkID)10280815(PQKB)11754336(DE-He213)978-3-540-45586-8(MiAaPQ)EBC3073333(PPN)155172352(EXLCZ)99100000000021164620121227d2001 u| 0engurnn|008mamaatxtccrComputational Combinatorial Optimization[electronic resource] Optimal or Provably Near-Optimal Solutions /edited by Michael Jünger, Denis Naddef1st ed. 2001.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2001.1 online resource (X, 310 p.) Lecture Notes in Computer Science,0302-9743 ;2241Bibliographic Level Mode of Issuance: Monograph3-540-42877-1 Includes bibliographical references at the end of each chapters and index.General 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.This 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.Lecture Notes in Computer Science,0302-9743 ;2241Mathematical optimizationComputer science—MathematicsAlgorithmsInformation technologyBusiness—Data processingData structures (Computer science)CombinatoricsOptimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26008Discrete Mathematics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17028Algorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021IT in Businesshttps://scigraph.springernature.com/ontologies/product-market-codes/522000Data Structureshttps://scigraph.springernature.com/ontologies/product-market-codes/I15017Combinatoricshttps://scigraph.springernature.com/ontologies/product-market-codes/M29010Mathematical optimization.Computer science—Mathematics.Algorithms.Information technology.Business—Data processing.Data structures (Computer science).Combinatorics.Optimization.Discrete Mathematics in Computer Science.Algorithm Analysis and Problem Complexity.IT in Business.Data Structures.Combinatorics.519.7Jünger Michaeledthttp://id.loc.gov/vocabulary/relators/edtNaddef Denisedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996465664603316Computational combinatorial optimization972204UNISA