LEADER 04037nam  22007095  450 
001 9910616395903321
005 20240222095239.0
010   $a3-031-10596-6
024 7 $a10.1007/978-3-031-10596-8
035   $a(MiAaPQ)EBC7100660
035   $a(Au-PeEL)EBL7100660
035   $a(CKB)24950006400041
035   $a(DE-He213)978-3-031-10596-8
035   $a(PPN)264954203
035   $a(EXLCZ)9924950006400041
100   $a20220926d2022      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aIntroduction to Combinatorial Optimization /$fby Ding-Zhu Du, Panos M. Pardalos, Xiaodong Hu, Weili Wu
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (407 pages)
225 1 $aSpringer Optimization and Its Applications,$x1931-6836 ;$v196
311 08$aPrint version: Du, Ding-Zhu Introduction to Combinatorial Optimization Cham : Springer International Publishing AG,c2022 9783031105944 
320   $aIncludes bibliographical references and index.
327   $a1. Introduction.-2. Divide-and-Conquer -- 3. Dynamic Programming and Shortest Path -- 4. Greedy Algorithm and Spanning Tree -- 5. Incremental Method and Maximum Network Flow -- 6. Linear Programming -- 7. Primal-Dual Methods and Minimum Cost Flow -- 8. NP-hard Problems and Approximation Algorithms -- 9. Restriction and Steiner Tree -- 10. Greedy Approximation and Submodular Optimization -- 11. Relaxation and Rounding. 12. Nonsubmodular Optimization -- Bibliography.
330   $aIntroductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, such as greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook.
410  0$aSpringer Optimization and Its Applications,$x1931-6836 ;$v196
606   $aMathematical optimization
606   $aComputer science
606   $aOperations research
606   $aManagement science
606   $aAlgorithms
606   $aOptimization
606   $aTheory of Computation
606   $aOperations Research, Management Science 
606   $aAlgorithms
606   $aOptimització combinatòria$2thub
608   $aLlibres electrònics$2thub
615  0$aMathematical optimization.
615  0$aComputer science.
615  0$aOperations research.
615  0$aManagement science.
615  0$aAlgorithms.
615 14$aOptimization.
615 24$aTheory of Computation.
615 24$aOperations Research, Management Science .
615 24$aAlgorithms.
615  7$aOptimització combinatòria
676   $a519.64
676   $a519.64
700   $aDu$b Dingzhu$061540
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910616395903321
996   $aIntroduction to combinatorial optimization$93039159
997   $aUNINA