Verfügbarkeit: Algorithm design | Technische Universität München

Algorithm design:

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Bibliographische Detailangaben
Beteiligte Personen:	Kleinberg, Jon 1971- (VerfasserIn), Tardos, Éva 1957- (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	Boston ; Munich [u.a.] Pearson/Addison-Wesley 2006
Ausgabe:	Pearson internat. ed.
Schlagwörter:	Computer algorithms Data structures (Computer science) Algorithmus Informatik
Links:	http://www.loc.gov/catdir/toc/ecip056/2005000401.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013835785&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung:	Includes bibliographical references (p. [805]-814) and index
Umfang:	XXIII, 838 S. ill. 24 cm
ISBN:	0321372913

Internformat

MARC


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Datensatz im Suchindex

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adam_text	Contents About the Authors v Preface xiii 1 Introduction: Some Representative Problems 1 1.1 A First Problem: Stable Matching 1 1.2 Five Representative Problems 12 Solved Exercises 19 Exercises 22 Notes and Further Reading 28 2 Basics of Algorithm Analysis 29 2.1 Computational Tractability 29 2.2 Asymptotic Order of Growth 35 2.3 Implementing the Stable Matching Algorithm Using Lists and Arrays 42 2.4 A Survey of Common Running Times 47 2.5 A More Complex Data Structure: Priority Queues 57 Solved Exercises 65 Exercises 67 Notes and Further Reading 70 3 Graphs 73 3.1 Basic Definitions and Applications 73 3.2 Graph Connectivity and Graph Traversal 78 3.3 Implementing Graph Traversal Using Queues and Stacks 87 3.4 Testing Bipartiteness: An Application of Breadth-First Search 94 3.5 Connectivity in Directed Graphs 97 3.6 Directed Acyclic Graphs and Topological Ordering 99 Solved Exercises 104 Exercises 107 Notes and Further Reading 112 Greedy Algorithms 115 4.1 Interval Scheduling: The Greedy Algorithm Stays Ahead 116 4.2 Scheduling to Minimize Lateness: An Exchange Argument 125 4.3 Optimal Caching: A More Complex Exchange Argument 131 4.4 Shortest Paths in a Graph 137 4.5 The Minimum Spanning Tree Problem 142 4.6 Implementing Kruskaľs Algorithm: The Union-Find Data Structure 151 4.7 Clustering 157 4.8 Huffman Codes and Data Compression 161 : 4.9 Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm 177 Solved Exercises 183 Exercises 188 Notes and Further Reading 205 Divide and Conquer 209 5.1 A First Recurrence: The Mergesort Algorithm 210 5.2 Further Recurrence Relations 214 5.3 Counting Inversions 221 5.4 Finding the Closest Pair of Points 225 5.5 Integer Multiplication 231 5.6 Convolutions and the Fast Fourier Transform 234 Solved Exercises 242 Exercises 246 Notes and Further Reading 249 Dynamic Programming 251 6.1 Weighted Interval Scheduling: A Recursive Procedure 252 6.2 Principles of Dynamic Programming: Memoization or Iteration over Subproblems 258 6.3 Segmented Least Squares: Multi-way Choices 261 Contents 6.4 Subset Sums and Knapsacks: Adding a Variable 266 6.5 RNA Secondary Structure: Dynamic Programming over Intervals 272 6.6 Sequence Alignment 278 6.7 Sequence Alignment in Linear Space via Divide and Conquer 284 6.8 Shortest Paths in a Graph 290 6.9 Shortest Paths and Distance Vector Protocols 297 * 6.10 Negative Cycles in a Graph 301 Solved Exercises 307 Exercises 312 Notes and Further Reading 335 7 Network Flow 337 7.1 The Maximum-Flow Problem and the Ford-Fulkerson Algorithm 338 7.2 Maximum Flows and Minimum Cuts in a Network 346 73 Choosing Good Augmenting Paths 352 * 7.4 The Preflow-Push Maximum-Flow Algorithm 357 7.5 A First Application: The Bipartite Matching Problem 367 7.6 Disjoint Paths in Directed and Undirected Graphs 373 7.7 Extensions to the Maximum-Flow Problem 378 7.8 Survey Design 384 7.9 Airline Scheduling 387 7.10 Image Segmentation 391 7.11 Project Selection 396 7.12 Baseball Elimination 400 * 7.13 A Further Direction: Adding Costs to the Matching Problem 404 Solved Exercises 411 Exercises 415 Notes and Further Reading 448 S NP and Computational Intractability 451 8.1 Polynomial-Time Reductions 452 8.2 Reductions via Gadgets : The Satisfiability Problem 459 8.3 Efficient Certification and the Definition of NP 463 8.4 NP-Complete Problems 466 8.5 Sequencing Problems 473 8.6 Partitioning Problems 481 8.7 Graph Coloring 485 8.8 Numerical Problems 490 8.9 Co-NP and the Asymmetry of NP 495 8.10 A Partial Taxonomy of Hard Problems 497 Solved Exercises 500 Exercises 505 Notes and Further Reading 529 9 PSPACE: A Class of Problems beyond NP 531 9.1 PSPACE 531 9.2 Some Hard Problems in PSPACE 533 9.3 Solving Quantified Problems and Games in Polynomial Space 536 9.4 Solving the Planning Problem in Polynomial Space 538 9.5 Proving Problems PSPACE-Complete 543 Solved Exercises 547 Exercises 550 Notes and Further Reading 551 10 Extending the Limits of Tractability 553 10.1 Finding Small Vertex Covers 554 10.2 Solving NP-Hard Problems on Trees 558 10.3 Coloring a Set of Circular Arcs 563 * 10.4 Tree Decompositions of Graphs 572 * 10.5 Constructing a Tree Decomposition 584 Solved Exercises 591 Exercises 594 Notes and Further Reading 598 11 Approximation Algorithms 599 11.1 Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem 600 11.2 The Center Selection Problem 606 11.3 Set Cover: A General Greedy Heuristic 612 11.4 The Pricing Method: Vertex Cover 618 11.5 Maximization via the Pricing Method: The Disjoint Paths Problem 624 11.6 Linear Programming and Rounding: An Application to Vertex Cover 630 * 11.7 Load Balancing Revisited: A More Advanced LP Application 637 Contents 11.8 Arbitrarily Good Approximations: The Knapsack Problem 644 Solved Exercises 649 Exercises 651 Notes and Further Reading 659 12 Local Search 661 12.1 The Landscape of an Optimization Problem 662 12.2 The Metropolis Algorithm and Simulated Annealing 666 12.3 An Application of Local Search to Hopfield Neural Networks 671 12.4 Maximum-Cut Approximation via Local Search 676 12.5 Choosing a Neighbor Relation 679 * 12.6 Classification via Local Search 681 12.7 Best-Response Dynamics and Nash Equilibria 690 Solved Exercises 700 Exercises 702 Notes and Further Reading 705 13 Randomized Algorithms 707 13.1 A First Application: Contention Resolution 708 13.2 Finding the Global Minimum Cut 714 13.3 Random Variables and Their Expectations 719 13.4 A Randomized Approximation Algorithm for MAX 3-SAT 724 13.5 Randomized Divide and Conquer: Median-Finding and Quicksort 727 13.6 Hashing: A Randomized Implementation of Dictionaries 734 13.7 Finding the Closest Pair of Points: A Randomized Approach 741 13.8 Randomized Caching 750 13.9 Chernoff Bounds 758 13.10 Load Balancing 760 13.11 Packet Routing 762 13.12 Background: Some Basic Probability Definitions 769 Solved Exercises 776 Exercises 782 Notes and Further Reading 793 Epilogue: Algorithms That Run Forever 795 References 805 Index 815
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spellingShingle	Kleinberg, Jon 1971- Tardos, Éva 1957- Algorithm design Computer algorithms Data structures (Computer science) Algorithmus (DE-588)4001183-5 gnd Informatik (DE-588)4026894-9 gnd
subject_GND	(DE-588)4001183-5 (DE-588)4026894-9
title	Algorithm design
title_auth	Algorithm design
title_exact_search	Algorithm design
title_full	Algorithm design Jon Kleinberg, Éva Tardos
title_fullStr	Algorithm design Jon Kleinberg, Éva Tardos
title_full_unstemmed	Algorithm design Jon Kleinberg, Éva Tardos
title_short	Algorithm design
title_sort	algorithm design
topic	Computer algorithms Data structures (Computer science) Algorithmus (DE-588)4001183-5 gnd Informatik (DE-588)4026894-9 gnd
topic_facet	Computer algorithms Data structures (Computer science) Algorithmus Informatik
url	http://www.loc.gov/catdir/toc/ecip056/2005000401.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013835785&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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