The.Algorithm.Design.Manual.Springer-Verlag.1998

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file:///E|/WEBSITE/BIBLIO/TESTDATA/AIRPLANE DL 464 ATL 1145A DCA 125P L 0 757 F Y B M Q NW1866 ATL 1240P DCA 216P L 0 D9S F Y B M H DL 402 ATL 120P DCA 259P L 0 757 F Y B M Q DL 378 ATL 319P DCA 455P 0 72S F Y B M Q DL 280 ATL 449P DCA 630P D 0 757 F Y B M Q NW1878 ATL 545P DCA 731P D 0 D9S F Y B M H DL 178 ATL 658P DCA 835P D 0 757 F Y B M Q DL 394 ATL 846P DCA 1025P 0 M80 F Y B M Q UA 717 ATL 640A DEN 804A B 0 737 F Y B M Q CO 275 ATL 650A DEN 810A B 0 733 Y Q H K B DL 445 ATL 857A DEN 1005A B 0 757 F Y B M Q DL 257 ATL 1159A DEN 105P L 0 72S F Y B M Q UA 373 ATL 310P DEN 429P S 0 737 F Y B M Q DL1668 ATL 312P DEN 415P S 0 72S F Y B M Q CO1759 ATL 400P DEN 520P D 0 733 A Y Q H K DL1055 ATL 652P DEN 1130P D 2 M80 F@ Y@ B@ M@ Q@ DL 675 ATL 709P DEN 830P D 0 757 F Y B M Q DL 785 ATL 625A DFW 735A B 0 757 FN YN BN MN QN AA 837 ATL 725A DFW 835A B 0 72S FN YN B H M DL 793 ATL 819A DFW 1055A # 1 763 F Y B M Q DL 444 ATL 819A DFW 1109A S 2 72S Y B M Q H DL 551 ATL 819A DFW 1110A S 2 M80 F Y B M Q DL 409 ATL 820A DFW 1108A # 2 M80 F Y B M Q DL 671 ATL 822A DFW 927A B 0 72S F Y B M Q DL 803 ATL 825A DFW 1055A S 1 73S F Y B M Q DL 357 ATL 826A DFW 1108A B 1 M80 F Y B M Q DL 239 ATL 833A DFW 1105A S 1 72S F Y B M Q DL 775 ATL 838A DFW 1108A S 1 73S F Y B M Q AA1683 ATL 840A DFW 1002A B 0 S80 F Y B H M DL 873 ATL 907A DFW 1108A 1 M80 F Y B M Q DL 17 ATL 1006A DFW 1110A S 0 L15 F Y B M Q DL1101 ATL 1144A DFW 1253P L 0 M80 F Y B M Q DL 307 ATL 1144A DFW 227P S 1 767 F Y B M H DL 545 ATL 1144A DFW 230P L 1 72S F Y B M Q DL 323 ATL 1144A DFW 230P 2 M80 F Y B M Q DL 125 ATL 1147A DFW 225P L 1 73S F Y B M Q DL1428 ATL 1149A DFW 222P L 1 72S F Y B M Q DL1137 ATL 1154A DFW 225P L 1 M80 F Y B M Q DL1045 ATL 1154A DFW 204P L 1 D9S F Y B M Q DL1457 ATL 1155A DFW 217P L 1 D9S F Y B M Q DL 946 ATL 1157A DFW 217P S 1 D9S F Y B M Q DL 299 ATL 1159A DFW 215P S 1 73S F Y B M Q DL 837 ATL 1203P DFW 217P S 1 M80 F Y B M Q AA 139 ATL 1225P DFW 143P L 0 72S F Y B H M DL 758 ATL 122P DFW 414P S 2 M80 F Y B M Q DL 179 ATL 124P DFW 230P L 0 L10 F Y B M Q TW 621 ATL 139P DFW 501P 1 D9S F Y B Q M AA 425 ATL 156P DFW 311P 0 S80 F Y B H M DL 145 ATL 310P DFW 422P S 0 767 F Y B M Q DL 719 ATL 310P DFW 606P S 1 M80 F Y B M Q DL1033 ATL 310P DFW 610P S 2 M80 F Y B M Q DL 557 ATL 312P DFW 611P S 2 757 F Y B M Q DL 139 ATL 314P DFW 553P 1 757 F Y B M H DL 847 ATL 323P DFW 555P 1 M80 F Y B M Q DL 691 ATL 325P DFW 611P 2 72S F Y B M Q DL1709 ATL 327P DFW 601P S 1 757 F Y B M Q DL 845 ATL 327P DFW 552P 1 73S F Y B M Q AA 385 ATL 430P DFW 547P S 0 S80 F Y B H M DL 195 ATL 449P DFW 605P D 0 L10 F Y B M Q DL1023 ATL 455P DFW 742P D 1 M80 F Y B M Q file:///E|/WEBSITE/BIBLIO/TESTDATA/AIRPLANE (5 of 67) [19/1/2003 1:40:22]
file:///E|/WEBSITE/BIBLIO/TESTDATA/AIRPLANE DL 405 ATL 641P DFW 755P D 0 M80 F Y B M DL1153 ATL 641P DFW 840P S 1 D9S F@ Y@ B@ M@ Q@ DL 817 ATL 642P DFW 940P 2 M80 F@ Y@ B@ M@ Q@ DL 397 ATL 649P DFW 936P D 1 M80 F@ Y@ B@ M@ Q@ DL1055 ATL 652P DFW 937P D 1 M80 F@ Y@ B@ M@ Q@ DL1002 ATL 653P DFW 937P # 2 M80 F@ Y@ B@ M@ Q@ DL1081 ATL 656P DFW 923P D 1 D9S F@ Y@ B@ M@ Q@ DL 883 ATL 656P DFW 925P D 1 73S F@ Y@ B@ M@ Q@ AA 701 ATL 700P DFW 832P D 0 S80 F YN B H M DL1507 ATL 702P DFW 946P S 1 757 F Y B M Q DL 593 ATL 703P DFW 917P S 1 D9S F@ Y@ B@ M@ Q@ DL 657 ATL 708P DFW 937P S 1 M80 F Y B M Q DL 970 ATL 743P DFW 939P 1 73S F@ Y@ B@ M@ Q@ DL 227 ATL 835P DFW 948P 0 763 FN YN BN MN QN DL 585 ATL 1015P DFW 1117P 0 M80 FN YN BN MN QN DL 955 ATL 1145P DFW 1245A 0 72S FN YN BN MN QN NW 492 ATL 640A DTW 829A B 0 DC9 FN YN BN M H DL 868 ATL 826A DTW 1010A B 0 72S F Y B M Q NW 494 ATL 950A DTW 1133A 0 72S FN YN BN M H DL 964 ATL 1004A DTW 1150A 0 M80 F Y B M Q NW 496 ATL 1250P DTW 234P L 0 D9S F Y B M H DL1044 ATL 127P DTW 315P L 0 M80 F Y B M Q NW 490 ATL 400P DTW 549P S 0 D9S F Y B M H DL 412 ATL 448P DTW 955P S 2 757 F Y B M Q DL 766 ATL 505P DTW 655P D 0 757 F Y B NW 498 ATL 555P DTW 745P D 0 D9S F Y B M H DL 256 ATL 859P DTW 1050P 0 763 F Y B M Q DL 714 ATL 1147P DTW 125A 0 M80 FN YN BN MN QN NW 823 ATL 820A HOU 1057A S 1 D9S F Y B M H DL1050 ATL 958A HOU 1100A S 0 D9S F Y B M Q DL 946 ATL 1157A HOU 403P S 2 D9S F Y B M Q DL1170 ATL 119P HOU 225P L 0 M80 F Y B M Q DL1023 ATL 455P HOU 605P D 0 M80 F Y B M Q DL 30 ATL 1230P JFK 238P L 0 L15 F C Y B M DL1916 ATL 145P JFK 353P L 0 310 F C Y B M TW 816 ATL 234P JFK 450P S 0 72S F C Y B Q HP 44 ATL 815A LAX 1125A B 1 320 F Y B H K DL1565 ATL 823A LAX 955A B 0 L10 F Y B M Q DL 369 ATL 828A LAX 1130A BS 1 757 F Y B M Q DL 269 ATL 1200N LAX 130P L 0 L10 F Y B M Q DL 179 ATL 124P LAX 440P LS 1 L10 F Y B M Q DL 139 ATL 314P LAX 920P D 3 757 F Y B M H DL 157 ATL 329P LAX 455P D 0 L10 F Y B M Q DL1049 ATL 457P LAX 630P D 0 L10 F Y B M Q DL 187 ATL 707P LAX 855P D 0 767 F Y B M Q DL 446 ATL 851P LAX 1040P S 0 757 F Y B M Q DL 143 ATL 1035P LAX 1210A S 0 757 FN YN BN MN QN DL 339 ATL 632A MIA 810A B 0 757 FN YN BN MN QN DL 321 ATL 819A MIA 1000A B 0 757 F Y B M AA 709 ATL 828A MIA 1015A B 0 727 F Y B M H PA 425 ATL 835A MIA 1019A # 0 72S F Y B M Q DL1155 ATL 1001A MIA 1145A 0 763 F Y B M H AA1555 ATL 1100A MIA 1243P 0 72S F Y B M H DL 449 ATL 1144A MIA 125P L 0 763 F Y AA 825 ATL 135P MIA 333P 0 72S F Y B M H DL 395 ATL 139P MIA 325P S 0 72S F Y B M H DL 472 ATL 326P MIA 515P 0 757 F Y B M H DL 491 ATL 659P MIA 845P D 0 767 F Y B M Q AA 471 ATL 730P MIA 926P D 0 72S F Y B M H DL 325 ATL 857P MIA 1035P 0 72S F Y B M Q DL 469 ATL 1022P MIA 1156P 0 72S FN YN BN MN QN file:///E|/WEBSITE/BIBLIO/TESTDATA/AIRPLANE (6 of 67) [19/1/2003 1:40:22]
Page 1 and 2:
The Algorithm Design Manual Next: P
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Preface Next: Acknowledgments Up: T
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Preface one stressing design over a
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Acknowledgments Mon Jun 2 23:33:50
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Contents Next: Techniques Up: The A
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Contents ■ All-Pairs Shortest Pat
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Contents ■ Graph Problems: Polyno
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Contents ● About this document ..
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The Algorithm Design Manual The Alg
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Lecture Notes -- Analysis of Algori
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Lecture Notes -- Analysis of Algori
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The Stony Brook Algorithm Repositor
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Techniques Next: Introduction to Al
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Techniques Algorithms Mon Jun 2 23:
Page 29 and 30:
Introduction to Algorithms ● Reas
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Data Structures and Sorting divide-
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Breaking Problems Down ● Dynamic
Page 35 and 36:
Graph Algorithms The take-home less
Page 37 and 38:
Combinatorial Search and Heuristic
Page 39 and 40:
Intractable Problems and Approximat
Page 41 and 42:
How to Design Algorithms Next: Reso
Page 43 and 44:
How to Design Algorithms with a cou
Page 45 and 46:
How to Design Algorithms Next: Reso
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A Catalog of Algorithmic Problems N
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A Catalog of Algorithmic Problems
Page 51 and 52:
Algorithmic Resources Next: Softwar
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References L. Adleman. Algorithmic
Page 55 and 56:
References AS89 Ata83 Ata84 problem
Page 57 and 58:
References BJL 91 A. Blum, T. Jiang
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References BS81 BS86 BS93 BS96 BS97
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References J. M. Chambers. Partial
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References CT80 CT92 1971. G. Carpa
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References K. Daniels and V. Milenk
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References (FOCS), pages 60-69, 199
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References FM71 M. Fischer and A. M
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References History of Computing, 7:
Page 73 and 74:
References N. Gibbs, W. Poole, and
Page 75 and 76:
References Hof82 Hof89 Hol75 C. M.
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References IK75 Ita78 O. Ibarra and
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References Kir83 D. Kirkpatrick. Ef
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References object in 2-dimensional
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References LT79 LT80 8:99-118, 1995
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References Mil97 V. Milenkovic. Dou
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References Theoretical Computer Sci
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References Pav82 T. Pavlidis. Algor
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References Rei72 Rei91 Rei94 E. Rei
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References Prentice Hall, Englewood
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References SR95 SS71 SS90 SSS74 ST8
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References Tin90 Mikkel Thorup. On
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References Wel84 T. Welch. A techni
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References Algorithms Mon Jun 2 23:
Page 103 and 104:
Correctness and Efficiency Next: Co
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Correctness NearestNeighborTSP(P) P
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Correctness Figure: A bad example f
Page 109 and 110:
Efficiency Next: Expressing Algorit
Page 111 and 112:
Keeping Score Next: The RAM Model o
Page 113 and 114:
The RAM Model of Computation substa
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Best, Worst, and Average-Case Compl
Page 117 and 118:
The Big Oh Notation Figure: Illustr
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Logarithms Next: Modeling the Probl
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Logarithms justified in ignoring th
Page 123 and 124:
Modeling the Problem Figure: Modeli
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About the War Stories Next: War Sto
Page 127 and 128:
War Story: Psychic Modeling Next: E
Page 129 and 130:
War Story: Psychic Modeling have pu
Page 131 and 132:
War Story: Psychic Modeling Next: E
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Exercises (b) If I prove that an al
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Fundamental Data Types Next: Contai
Page 137 and 138:
Containers Next: Dictionaries Up: F
Page 139 and 140:
Dictionaries Next: Binary Search Tr
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Binary Search Trees BinaryTreeQuery
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Priority Queues Next: Specialized D
Page 145 and 146:
Specialized Data Structures Next: S
Page 147 and 148:
Sorting Next: Applications of Sorti
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Applications of Sorting Figure: Con
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Data Structures Next: Incremental I
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Incremental Insertion Next: Divide
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Randomization Next: Bucketing Techn
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Randomization Next: Bucketing Techn
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Bucketing Techniques Algorithms Mon
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War Story: Stripping Triangulations
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War Story: Stripping Triangulations
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War Story: Mystery of the Pyramids
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War Story: Mystery of the Pyramids
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War Story: String 'em Up We were co
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War Story: String 'em Up Figure: Su
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Exercises Next: Implementation Chal
Page 175 and 176:
Exercises used to select the pivot.
Page 177 and 178:
Dynamic Programming Next: Fibonacci
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Fibonacci numbers Next: The Partiti
Page 181 and 182:
Fibonacci numbers Next: The Partiti
Page 183 and 184:
The Partition Problem . What is the
Page 185 and 186:
The Partition Problem Figure: Dynam
Page 187 and 188:
Approximate String Matching Next: L
Page 189 and 190:
Approximate String Matching The val
Page 191 and 192:
Longest Increasing Sequence Will th
Page 193 and 194:
Minimum Weight Triangulation Next:
Page 195 and 196:
Limitations of Dynamic Programming
Page 197 and 198:
War Story: Evolution of the Lobster
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War Story: Evolution of the Lobster
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War Story: What's Past is Prolog Ne
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War Story: What's Past is Prolog th
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War Story: Text Compression for Bar
Page 207 and 208:
War Story: Text Compression for Bar
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Divide and Conquer Next: Fast Expon
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Fast Exponentiation Next: Binary Se
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Binary Search Next: Square and Othe
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Page 217 and 218:
Exercises whose denominations are ,
Page 219 and 220:
The Friendship Graph Next: Data Str
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The Friendship Graph friendship gra
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Data Structures for Graphs linked t
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War Story: Getting the Graph ``Well
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Traversing a Graph Next: Breadth-Fi
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Breadth-First Search Next: Depth-Fi
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Depth-First Search Next: Applicatio
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Depth-First Search Next: Applicatio
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Connected Components Next: Tree and
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Two-Coloring Graphs Next: Topologic
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Topological Sorting Next: Articulat
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Modeling Graph Problems Next: Minim
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Modeling Graph Problems good line s
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Minimum Spanning Trees ● Prim's A
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Prim's Algorithm inserted edge (x,y
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Kruskal's Algorithm a tree of weigh
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Dijkstra's Algorithm Next: All-Pair
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All-Pairs Shortest Path Next: War S
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War Story: Nothing but Nets Next: W
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War Story: Nothing but Nets ``You a
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War Story: Dialing for Documents Ne
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War Story: Dialing for Documents If
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War Story: Dialing for Documents CO
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Exercises Prove the statement or gi
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Backtracking report it. kth element
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Constructing All Subsets Next: Cons
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Constructing All Paths in a Graph N
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Search Pruning Next: Bandwidth Mini
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Bandwidth Minimization immediately
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War Story: Covering Chessboards Nex
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War Story: Covering Chessboards att
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Heuristic Methods Mon Jun 2 23:33:5
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Simulated Annealing Return S then u
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Traveling Salesman Problem Next: Ma
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Independent Set Next: Circuit Board
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Neural Networks Next: Genetic Algor
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Genetic Algorithms Next: War Story:
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War Story: Annealing Arrays Next: P
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War Story: Annealing Arrays optimal
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Parallel Algorithms Next: War Story
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War Story: Going Nowhere Fast Next:
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Page 305 and 306:
Problems and Reductions Next: Simpl
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Simple Reductions Next: Hamiltonian
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Hamiltonian Cycles Next: Independen
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Independent Set and Vertex Cover pr
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Clique and Independent Set These la
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Satisfiability Mon Jun 2 23:33:50 E
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The Theory of NP-Completeness Next:
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3-Satisfiability where for , , , an
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Integer Programming Next: Vertex Co
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Integer Programming possible IP ins
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Vertex Cover reduction for the 3-SA
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Other NP-Complete Problems hard. Th
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The Art of Proving Hardness easiest
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War Story: Hard Against the Clock N
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War Story: Hard Against the Clock I
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Approximation Algorithms Next: Appr
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Approximating Vertex Cover Next: Th
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The Euclidean Traveling Salesman Ne
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The Euclidean Traveling Salesman Ne
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Exercises 1. Prove that the low deg
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Data Structures Next: Dictionaries
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Dictionaries Next: Priority Queues
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Dictionaries use a function that ma
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Dictionaries Implementation-oriente
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Priority Queues ● Besides access
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Priority Queues Fibonacci heaps [FT
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Suffix Trees and Arrays Figure: A t
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Suffix Trees and Arrays [GBY91]. Se
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Graph Data Structures algorithms).
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Graph Data Structures including the
Page 365 and 366:
Set Data Structures Next: Kd-Trees
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Set Data Structures parent pointers
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Kd-Trees Next: Numerical Problems U
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Kd-Trees about p. Say we are lookin
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Numerical Problems Next: Solving Li
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Numerical Problems Mon Jun 2 23:33:
Page 377 and 378:
Solving Linear Equations algorithm
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Solving Linear Equations Matrix inv
Page 381 and 382:
Bandwidth Reduction images near eac
Page 383 and 384:
Matrix Multiplication Next: Determi
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Matrix Multiplication The linear al
Page 387 and 388:
Determinants and Permanents Next: C
Page 389 and 390:
Determinants and Permanents exposit
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Constrained and Unconstrained Optim
Page 393 and 394:
Constrained and Unconstrained Optim
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Linear Programming variable assignm
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Linear Programming The book [MW93]
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Random Number Generation Next: Fact
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Random Number Generation is largely
Page 403 and 404:
Random Number Generation Related Pr
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Factoring and Primality Testing The
Page 407 and 408:
Factoring and Primality Testing Alg
Page 409 and 410:
Arbitrary-Precision Arithmetic If y
Page 411 and 412:
Arbitrary-Precision Arithmetic PARI
Page 413 and 414:
Knapsack Problem Next: Discrete Fou
Page 415 and 416:
Knapsack Problem is a subset of S'
Page 417 and 418:
Discrete Fourier Transform Next: Co
Page 419 and 420:
Discrete Fourier Transform an algor
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Combinatorial Problems Next: Sortin
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Sorting Next: Searching Up: Combina
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Sorting The simplest approach to ex
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Sorting operations, implying an sor
Page 429 and 430:
Searching large performance improve
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Searching Notes: Mehlhorn and Tsaka
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Median and Selection followed by fi
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Generating Permutations Next: Gener
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Generating Permutations The rank/un
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Generating Permutations generating
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Generating Subsets look right when
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Generating Subsets above for detail
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Generating Partitions Although the
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Generating Partitions Two related c
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Generating Graphs generate: ● Do
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Generating Graphs Combinatorica [Sk
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Calendrical Calculations Next: Job
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Calendrical Calculations Gregorian,
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Job Scheduling ● To assign a set
Page 459 and 460:
Job Scheduling shop scheduling incl
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Satisfiability logic, and automatic
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Satisfiability Next: Graph Problems
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Graph Problems: Polynomial-Time rec
Page 467 and 468:
Connected Components Testing the co
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Connected Components discussing gra
Page 471 and 472:
Topological Sorting contradiction t
Page 473 and 474:
Minimum Spanning Tree Next: Shortes
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Minimum Spanning Tree help you sort
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Shortest Path Next: Transitive Clos
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Shortest Path easier to program tha
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Shortest Path Related Problems: Net
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Transitive Closure and Reduction
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Transitive Closure and Reduction Al
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Matching augmenting paths and stopp
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Matching Combinatorica [Ski90] prov
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Eulerian Cycle / Chinese Postman ar
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Eulerian Cycle / Chinese Postman Ne
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Edge and Vertex Connectivity Severa
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Edge and Vertex Connectivity Next:
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Network Flow programming model for
Page 501 and 502:
Network Flow Combinatorica [Ski90]
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Drawing Graphs Nicely vertices are
Page 505 and 506:
Drawing Graphs Nicely labs.com/orgs
Page 507 and 508:
Drawing Trees such as the map of th
Page 509 and 510:
Planarity Detection and Embedding N
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Planarity Detection and Embedding p
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Graph Problems: Hard Problems ● C
Page 515 and 516:
Clique approximate even to within a
Page 517 and 518:
Independent Set Next: Vertex Cover
Page 519 and 520:
Independent Set Related Problems: C
Page 521 and 522:
Vertex Cover Vertex cover and indep
Page 523 and 524:
Traveling Salesman Problem Next: Ha
Page 525 and 526:
Traveling Salesman Problem practice
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Traveling Salesman Problem Size is
Page 529 and 530:
Hamiltonian Cycle Eulerian cycle, p
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Graph Partition Next: Vertex Colori
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Graph Partition annealing, is almos
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Vertex Coloring Several special cas
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Vertex Coloring Notes: An excellent
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Edge Coloring The minimum number of
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Graph Isomorphism Next: Steiner Tre
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Graph Isomorphism vertices into equ
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Steiner Tree Next: Feedback Edge/Ve
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Steiner Tree The worst case for a m
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Feedback Edge/Vertex Set Next: Comp
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Feedback Edge/Vertex Set An interes
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Computational Geometry complete bib
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Robust Geometric Primitives Next: C
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Robust Geometric Primitives ● Are
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Robust Geometric Primitives Related
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Convex Hull ● How many dimensions
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Convex Hull http://www.cs.att.com/n
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Triangulation Next: Voronoi Diagram
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Triangulation GEOMPACK is a suite o
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Voronoi Diagrams Next: Nearest Neig
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Voronoi Diagrams McDonald's, the ti
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Nearest Neighbor Search Next: Range
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Nearest Neighbor Search Implementat
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Range Search Next: Point Location U
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Range Search subdivisions in C++. I
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Point Location the n edges for inte
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Point Location More recently, there
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Intersection Detection ● Do you w
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Intersection Detection Implementati
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Bin Packing Next: Medial-Axis Trans
Page 591 and 592:
Bin Packing approach for general sh
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Medial-Axis Transformation Next: Po
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Medial-Axis Transformation Implemen
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Polygon Partitioning number of piec
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Simplifying Polygons Next: Shape Si
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Simplifying Polygons vertices and o
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Shape Similarity Next: Motion Plann
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Shape Similarity or how close it is
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Motion Planning There is a wide ran
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Motion Planning often arise in the
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Maintaining Line Arrangements Think
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Maintaining Line Arrangements Next:
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Minkowski Sum where x+y is the vect
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Set and String Problems Next: Set C
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Set Cover Next: Set Packing Up: Set
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Set Cover Figure: Hitting set is du
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Set Packing Next: String Matching U
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Set Packing Notes: An excellent exp
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String Matching shouldn't try. Furt
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String Matching and texts, I recomm
Page 631 and 632:
Approximate String Matching This sa
Page 633 and 634:
Approximate String Matching http://
Page 635 and 636:
Text Compression Next: Cryptography
Page 637 and 638:
Text Compression code string. ASCII
Page 639 and 640:
Cryptography Next: Finite State Mac
Page 641 and 642:
Cryptography ● How can I validate
Page 643 and 644:
Cryptography MD5 [Riv92] is the sec
Page 645 and 646:
Finite State Machine Minimization F
Page 647 and 648:
Finite State Machine Minimization S
Page 649 and 650:
Longest Common Substring than edit
Page 651 and 652:
Longest Common Substring include [A
Page 653 and 654:
Shortest Common Superstring Finding
Page 655 and 656:
Software systems Next: LEDA Up: Alg
Page 657 and 658:
LEDA Next: Netlib Up: Software syst
Page 659 and 660:
Netlib Algorithms Mon Jun 2 23:33:5
Page 661 and 662:
The Stanford GraphBase Next: Combin
Page 663 and 664:
Algorithm Animations with XTango Ne
Page 665 and 666:
Programs from Books Next: Discrete
Page 667 and 668:
Handbook of Data Structures and Alg
Page 669 and 670:
Algorithms from P to NP Next: Compu
Page 671 and 672:
Algorithms in C++ Next: Data Source
Page 673 and 674:
Textbooks Next: On-Line Resources U
Page 675 and 676:
On-Line Resources Next: Literature
Page 677 and 678:
People Next: Software Up: On-Line R
Page 679 and 680:
Professional Consulting Services Ne
Page 681 and 682:
Index A Up: Index - All Index: A ab
Page 683 and 684:
Index A artists steal ASA ASCII asp
Page 685 and 686:
Index B binary representation - sub
Page 687 and 688:
Index C Up: Index - All Index: C C+
Page 689 and 690:
Index C clustering , , co-NP coding
Page 691 and 692:
Index C consulting services , conta
Page 693 and 694:
Index D Up: Index - All Index: D DA
Page 695 and 696:
Index D Dictionaries dictionaries -
Page 697 and 698:
Index D dynamic programming - appli
Page 699 and 700:
Index E empirical results - heurist
Page 701 and 702:
Index F Up: Index - All Index: F fa
Page 703 and 704:
Index F frequency domain friend-or-
Page 705 and 706:
Index G geometric shortest path , g
Page 707 and 708:
Index H Up: Index - All Index: H ha
Page 709 and 710:
Index H Algorithms Tue Jun 3 11:59:
Page 711 and 712:
Index I independent set - alternate
Page 713 and 714:
Index J Up: Index - All Index: J ji
Page 715 and 716:
Index K Algorithms Tue Jun 3 11:59:
Page 717 and 718:
Index L linear congruential generat
Page 719 and 720:
Index M Up: Index - All Index: M ma
Page 721 and 722:
Index M mindset minima minimax sear
Page 723 and 724:
Index N Up: Index - All Index: N na
Page 725 and 726:
Index N numerical analysis numerica
Page 727 and 728:
Index O overlap graph overpasses -
Page 729 and 730:
Index P , , , , , , , , , , passwor
Page 731 and 732:
Index P polygons polygon triangulat
Page 733 and 734:
Index Q Up: Index - All Index: Q Qh
Page 735 and 736:
Index R ranking combinatorial objec
Page 737 and 738:
Index S Up: Index - All Index: S s-
Page 739 and 740:
Index S Shape Similarity shape simp
Page 741 and 742:
Index S solar year Solving Linear E
Page 743 and 744:
Index S straight-line graph drawing
Page 745 and 746:
Index T Up: Index - All Index: T ta
Page 747 and 748:
Index T trees - matching trees - pa
Page 749 and 750:
Index V Up: Index - All Index: V va
Page 751 and 752:
Index W Up: Index - All Index: W wa
Page 753 and 754:
Index Y Up: Index - All Index: Y Yo
Page 755 and 756:
Index (complete) Up: Index - All In
Page 757 and 758:
Index (complete) arm, robot around
Page 759 and 760:
Index (complete) binary search tree
Page 761 and 762:
Index (complete) center vertex, , C
Page 763 and 764:
Index (complete) compaction compari
Page 765 and 766:
Index (complete) counting paths, co
Page 767 and 768:
Index (complete) deletion from bina
Page 769 and 770:
Index (complete) dominance ordering
Page 771 and 772:
Index (complete) English to French
Page 773 and 774:
Index (complete) file directory tre
Page 775 and 776:
Index (complete) geom.bib, geometri
Page 777 and 778:
Index (complete) Hamiltonian Cycle
Page 779 and 780:
Index (complete) implementation cha
Page 781 and 782:
Index (complete) job-shop schedulin
Page 783 and 784:
Index (complete) linear programming
Page 785 and 786:
Index (complete) , , , , , , , math
Page 787 and 788:
Index (complete) modular arithmetic
Page 789 and 790:
Index (complete) normal distributio
Page 791 and 792:
Index (complete) parallel algorithm
Page 793 and 794:
Index (complete) planar subdivision
Page 795 and 796:
Index (complete) proof of correctne
Page 797 and 798:
Index (complete) regular expression
Page 799 and 800:
Index (complete) self-organizing tr
Page 801 and 802:
Index (complete) sine functions sin
Page 803 and 804:
Index (complete) spring embedding h
Page 805 and 806:
Index (complete) Symbol Technologie
Page 807 and 808:
Index (complete) trial division Tri
Page 809 and 810:
Index (complete) VLSI circuit layou
Page 811 and 812:
1.4.4 Shortest Path 1.4.4 Shortest
Page 813 and 814:
1.2.5 Constrained and Unconstrained
Page 815 and 816:
1.6.4 Voronoi Diagrams 1.6.4 Vorono
Page 817 and 818:
1.4.7 Eulerian Cycle / Chinese Post
Page 819 and 820:
Online Bibliographies Online Biblio
Page 821 and 822:
About the Book -- The Algorithm Des
Page 823 and 824:
Copyright and Disclaimers Copyright
Page 825 and 826:
CD-ROM Installation Installation an
Page 827 and 828:
CD-ROM Installation install a sound
Page 829 and 830:
Thanks! Frank Ruscica file:///E|/WE
Page 831 and 832:
Thanks! Zhong Li Thanks also to Fil
Page 833 and 834:
CD-ROM Installation To use the CD-R
Page 835 and 836:
Binary Search in Action Binary Sear
Page 837 and 838:
Binary Search in Action file:///E|/
Page 839 and 840:
Binary Search in Action file:///E|/
Page 841 and 842:
Postscript version of the lecture n
Page 843 and 844:
Lecture 1 - analyzing algorithms Ne
Page 845 and 846:
Lecture 1 - analyzing algorithms Yo
Page 847 and 848:
Lecture 1 - analyzing algorithms Th
Page 849 and 850:
Lecture 1 - analyzing algorithms Th
Page 851 and 852:
Lecture 1 - analyzing algorithms is
Page 853 and 854:
Lecture 2 - asymptotic notation How
Page 855 and 856:
Lecture 2 - asymptotic notation Not
Page 857 and 858:
Lecture 2 - asymptotic notation alg
Page 859 and 860:
Lecture 2 - asymptotic notation Sup
Page 861 and 862:
Lecture 2 - asymptotic notation Nex
Page 863 and 864:
Lecture 3 - recurrence relations Is
Page 865 and 866:
Lecture 3 - recurrence relations
Page 867 and 868:
Lecture 3 - recurrence relations Li
Page 869 and 870:
Lecture 3 - recurrence relations Su
Page 871 and 872:
Lecture 3 - recurrence relations A
Page 873 and 874:
Lecture 4 - heapsort Note iteration
Page 875 and 876:
Lecture 4 - heapsort The convex hul
Page 877 and 878:
Lecture 4 - heapsort 1. All leaves
Page 879 and 880:
Lecture 4 - heapsort left = 2i righ
Page 881 and 882:
Lecture 4 - heapsort Since this sum
Page 883 and 884:
Lecture 4 - heapsort Selection sort
Page 885 and 886:
Lecture 4 - heapsort Greedy Algorit
Page 887 and 888:
Lecture 5 - quicksort Partitioning
Page 889 and 890:
Lecture 5 - quicksort Listen To Par
Page 891 and 892:
Lecture 5 - quicksort Listen To Par
Page 893 and 894:
Lecture 5 - quicksort The worst cas
Page 895 and 896:
Lecture 5 - quicksort Mon Jun 2 09:
Page 897 and 898:
Lecture 6 - linear sorting Since 2i
Page 899 and 900:
Lecture 6 - linear sorting With uni
Page 901 and 902:
Lecture 6 - linear sorting Listen T
Page 903 and 904:
Lecture 7 - elementary data structu
Page 905 and 906:
Page 907 and 908:
Page 909 and 910:
Page 911 and 912:
Page 913 and 914:
Page 915 and 916:
Page 917 and 918:
Lecture 8 - binary trees - Joyce Ki
Page 919 and 920:
Lecture 8 - binary trees TREE-MINIM
Page 921 and 922:
Lecture 8 - binary trees Inorder-Tr
Page 923 and 924:
Lecture 8 - binary trees Listen To
Page 925 and 926:
Lecture 8 - binary trees insert(b)
Page 927 and 928:
Lecture 8 - binary trees Not (1) -
Page 929 and 930:
Lecture 9 - catch up Next: Lecture
Page 931 and 932:
Lecture 10 - tree restructuring 1.
Page 933 and 934:
Lecture 10 - tree restructuring Lis
Page 935 and 936:
Lecture 10 - tree restructuring Not
Page 937 and 938:
Lecture 10 - tree restructuring Cas
Page 939 and 940:
Lecture 11 - backtracking Next: Lec
Page 941 and 942:
Lecture 11 - backtracking Only 63 s
Page 943 and 944:
Lecture 11 - backtracking Recursion
Page 945 and 946:
Lecture 11 - backtracking Specifica
Page 947 and 948:
Lecture 12 - introduction to dynami
Page 949 and 950:
Page 951 and 952:
Page 953 and 954:
Page 955 and 956:
Page 957 and 958:
Lecture 13 - dynamic programming ap
Page 959 and 960:
Page 961 and 962:
Page 963 and 964:
Lecture 14 - data structures for gr
Page 965 and 966:
Page 967 and 968:
Page 969 and 970:
Page 971 and 972:
Page 973 and 974:
Page 975 and 976:
Lecture 15 - DFS and BFS Next: Lect
Page 977 and 978:
Lecture 15 - DFS and BFS In a DFS o
Page 979 and 980:
Lecture 15 - DFS and BFS It could u
Page 981 and 982:
Lecture 15 - DFS and BFS Algorithm
Page 983 and 984:
Lecture 16 - applications of DFS an
Page 985 and 986:
Page 987 and 988:
Page 989 and 990:
Lecture 17 - minimum spanning trees
Page 991 and 992:
Page 993 and 994:
Page 995 and 996:
Page 997 and 998:
Page 999 and 1000:
Lecture 18 - shortest path algorthm
Page 1001 and 1002:
Page 1003 and 1004:
Page 1005 and 1006:
Page 1007 and 1008:
Page 1009 and 1010:
Lecture 19 - satisfiability Next: L
Page 1011 and 1012:
Lecture 19 - satisfiability Why? Th
Page 1013 and 1014:
Lecture 19 - satisfiability between
Page 1015 and 1016:
Lecture 19 - satisfiability Note th
Page 1017 and 1018:
Lecture 20 - integer programming Ex
Page 1019 and 1020:
Lecture 20 - integer programming Ne
Page 1021 and 1022:
Lecture 21 - vertex cover Proof: VC
Page 1023 and 1024:
Lecture 21 - vertex cover Question:
Page 1025 and 1026:
Lecture 21 - vertex cover seen to d
Page 1027 and 1028:
Lecture 22 - techniques for proving
Page 1029 and 1030:
Page 1031 and 1032:
Page 1033 and 1034:
Page 1035 and 1036:
Lecture 23 - approximation algorith
Page 1037 and 1038:
Page 1039 and 1040:
Page 1041 and 1042:
Page 1043 and 1044:
Page 1045 and 1046:
About this document ... Up: No Titl
Page 1047 and 1048:
1.1.6 Kd-Trees ● Point Location
Page 1049 and 1050:
1.1.3 Suffix Trees and Arrays Send
Page 1051 and 1052:
1.5.1 Clique ● Vertex Cover Go to
Page 1053 and 1054:
1.6.2 Convex Hull Related Problems
Page 1055 and 1056:
Visual Links Index file:///E|/WEBSI
Page 1057 and 1058:
Page 1059 and 1060:
Page 1061 and 1062:
Page 1063 and 1064:
Page 1065 and 1066:
Page 1067 and 1068:
Page 1069 and 1070:
Page 1071 and 1072:
Page 1073 and 1074:
Page 1075 and 1076:
Page 1077 and 1078:
Page 1079 and 1080:
Page 1081 and 1082:
Page 1083 and 1084:
About the Ratings About the Ratings
Page 1085 and 1086:
1.2 Numerical Problems 1.2 Numerica
Page 1087 and 1088:
1.4 Graph Problems -- polynomial-ti
Page 1089 and 1090:
1.6 Computational Geometry 1.6 Comp
Page 1091 and 1092:
C++ Language Implementations Algori
Page 1093 and 1094:
C Language Implementations ● POSI
Page 1095 and 1096:
FORTRAN Language Implementations Al
Page 1097 and 1098:
Lisp Language Implementations Algor
Page 1099 and 1100:
Algorithm Repository -- Citations C
Page 1101 and 1102:
Practical Algorithm Design -- User
Page 1103 and 1104:
LEDA - A Library of Efficient Data
Page 1105 and 1106:
Discrete Optimization Methods Discr
Page 1107 and 1108:
Netlib / TOMS -- Collected Algorith
Page 1109 and 1110:
Netlib / TOMS -- Collected Algorith
Page 1111 and 1112:
Xtango and Polka Algorithm Animatio
Page 1113 and 1114:
Combinatorica Combinatorica Combina
Page 1115 and 1116:
file:///E|/WEBSITE/IMPLEMEN/GRAPHBA
Page 1117 and 1118:
1.4.1 Connected Components 1.4.1 Co
Page 1119 and 1120:
1.5.9 Graph Isomorphism 1.5.9 Graph
Page 1121 and 1122:
1.2.3 Matrix Multiplication 1.2.3 M
Page 1123 and 1124:
1.6.14 Motion Planning 1.6.14 Motio
Page 1125 and 1126:
1.4.9 Network Flow 1.4.9 Network Fl
Page 1127 and 1128:
1.1.2 Priority Queues 1.1.2 Priorit
Page 1129 and 1130:
1.5.10 Steiner Tree 1.5.10 Steiner
Page 1131 and 1132:
1.4.5 Transitive Closure and Reduct
Page 1133 and 1134:
Page 1135 and 1136:
Page 1137 and 1138:
Genocop -- Optimization via Genetic
Page 1139 and 1140:
1.2.6 Linear Programming ● Knapsa
Page 1141 and 1142:
1.2.7 Random Number Generation ●
Page 1143 and 1144:
1.3.10 Satisfiability ● Constrain
Page 1145 and 1146:
Qhull - higher dimensional convex h
Page 1147 and 1148:
1.6.5 Nearest Neighbor Search 1.6.5
Page 1149 and 1150:
1.6.7 Point Location 1.6.7 Point Lo
Page 1151 and 1152:
1.6.10 Medial-Axis Transformation 1
Page 1153 and 1154:
1.6.3 Triangulation 1.6.3 Triangula
Page 1155 and 1156:
Nijenhuis and Wilf: Combinatorial A
Page 1157 and 1158:
1.5.5 Hamiltonian Cycle 1.5.5 Hamil
Page 1159 and 1160:
1.4.6 Matching 1.4.6 Matching INPUT
Page 1161 and 1162:
A compendium of NP optimization pro
Page 1163 and 1164:
1.6.9 Bin Packing 1.6.9 Bin Packing
Page 1165 and 1166:
1.6.12 Simplifying Polygons 1.6.12
Page 1167 and 1168:
1.6.13 Shape Similarity 1.6.13 Shap
Page 1169 and 1170:
1.6.11 Polygon Partitioning 1.6.11
Page 1171 and 1172:
1.4.3 Minimum Spanning Tree 1.4.3 M
Page 1173 and 1174:
1.6.15 Maintaining Line Arrangement
Page 1175 and 1176:
1.3.7 Generating Graphs 1.3.7 Gener
Page 1177 and 1178:
1.2.11 Discrete Fourier Transform 1
Page 1179 and 1180:
1.5.8 Edge Coloring 1.5.8 Edge Colo
Page 1181 and 1182:
1.3.3 Median and Selection 1.3.3 Me
Page 1183 and 1184:
1.3.1 Sorting 1.3.1 Sorting INPUT O
Page 1185 and 1186:
Plugins for use with the CDROM Plug
Page 1187 and 1188:
Implementation Challenges Next: Dat
Page 1189 and 1190:
Implementation Challenges Next: Gra
Page 1191 and 1192:
Implementation Challenges Next: Int
Page 1193 and 1194:
Caveats Next: Data Structures Up: A
Page 1195 and 1196:
1.1.1 Dictionaries ● Priority Que
Page 1197 and 1198:
1.1.4 Graph Data Structures ● Gra
Page 1199 and 1200:
1.1.5 Set Data Structures ● Gener
Page 1201 and 1202:
1.2.1 Solving Linear Equations ●
Page 1203 and 1204:
1.2.2 Bandwidth Reduction ● Topol
Page 1205 and 1206:
1.2.4 Determinants and Permanents
Page 1207 and 1208:
1.2.8 Factoring and Primality Testi
Page 1209 and 1210:
1.2.9 Arbitrary Precision Arithmeti
Page 1211 and 1212:
1.2.10 Knapsack Problem ● Linear
Page 1213 and 1214:
1.3.2 Searching ● Sorting Go to t
Page 1215 and 1216:
1.3.4 Generating Permutations ● C
Page 1217 and 1218:
1.3.5 Generating Subsets ● Genera
Page 1219 and 1220:
1.3.6 Generating Partitions ● Gen
Page 1221 and 1222:
1.3.8 Calendrical Calculations Go t
Page 1223 and 1224:
1.3.9 Job Scheduling ● Feedback E
Page 1225 and 1226:
1.4.2 Topological Sorting Related P
Page 1227 and 1228:
1.4.8 Edge and Vertex Connectivity
Page 1229 and 1230:
1.4.10 Drawing Graphs Nicely ● Pl
Page 1231 and 1232:
1.4.11 Drawing Trees ● Planarity
Page 1233 and 1234:
1.4.12 Planarity Detection and Embe
Page 1235 and 1236:
1.5.2 Independent Set ● Vertex Co
Page 1237 and 1238:
1.5.3 Vertex Cover ● Independent
Page 1239 and 1240:
1.5.4 Traveling Salesman Problem
Page 1241 and 1242:
1.5.6 Graph Partition ● Network F
Page 1243 and 1244:
1.5.7 Vertex Coloring Related Probl
Page 1245 and 1246:
1.5.11 Feedback Edge/Vertex Set Go
Page 1247 and 1248:
1.6.1 Robust Geometric Primitives G
Page 1249 and 1250:
1.6.6 Range Search ● Kd-Trees ●
Page 1251 and 1252:
1.6.8 Intersection Detection ● Ro
Page 1253 and 1254:
1.6.16 Minkowski Sum Go to the corr
Page 1255 and 1256:
1.7.1 Set Cover ● Set Packing ●
Page 1257 and 1258:
1.7.2 Set Packing Go to the corresp
Page 1259 and 1260:
1.7.3 String Matching ● Approxima
Page 1261 and 1262:
1.7.4 Approximate String Matching
Page 1263 and 1264:
1.7.5 Text Compression Go to the co
Page 1265 and 1266:
1.7.6 Cryptography ● Text Compres
Page 1267 and 1268:
1.7.7 Finite State Machine Minimiza
Page 1269 and 1270: 1.7.8 Longest Common Substring ●
Page 1271 and 1272: 1.7.9 Shortest Common Superstring G
Page 1273 and 1274: Handbook of Algorithms and Data Str
Page 1275 and 1276: Moret and Shapiro's Algorithms P to
Page 1277 and 1278: Index B Up: Index - All Index: B ba
Page 1279 and 1280: Index C Up: Index - All Index: C ch
Page 1281 and 1282: Index E Up: Index - All Index: E ed
Page 1283 and 1284: Index G Up: Index - All Index: G ga
Page 1285 and 1286: Index I Up: Index - All Index: I in
Page 1287 and 1288: Index L Up: Index - All Index: L li
Page 1289 and 1290: Index N Up: Index - All Index: N ne
Page 1291 and 1292: Index P Up: Index - All Index: P pa
Page 1293 and 1294: Index R Up: Index - All Index: R RA
Page 1295 and 1296: Index S successor supercomputer , s
Page 1297 and 1298: Index U Up: Index - All Index: U un
Page 1299 and 1300: Index W Up: Index - All Index: W wo
Page 1301 and 1302: Index (complete) bin packing bipart
Page 1303 and 1304: Index (complete) Fourier transform
Page 1305 and 1306: Index (complete) parenthesization p
Page 1307 and 1308: Index (complete) symmetry, exploiti
Page 1309 and 1310: Ranger - Nearest Neighbor Search in
Page 1311 and 1312: DIMACS Implementation Challenges Pe
Page 1313 and 1314: Stony Brook Project Implementations
Page 1315 and 1316: Clarkson's higher dimensional conve
Page 1317 and 1318: file:///E|/WEBSITE/BIBLIO/TESTDATA/
Page 1319: file:///E|/WEBSITE/BIBLIO/TESTDATA/
Page 1371 and 1372:
file:///E|/WEBSITE/BIBLIO/TESTDATA/
Page 1373 and 1374:
Page 1375 and 1376:
Page 1377 and 1378:
Page 1379 and 1380:
Page 1381 and 1382:
Page 1383 and 1384:
Page 1385 and 1386:
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Page 1391 and 1392:
Page 1393 and 1394:
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Page 1403 and 1404:
Page 1405 and 1406:
Page 1407 and 1408:
Page 1409 and 1410:
Page 1411 and 1412:
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Page 1429 and 1430:
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Page 1435 and 1436:
Page 1437 and 1438:
Page 1439 and 1440:
Page 1441 and 1442:
Page 1443 and 1444:
Page 1445 and 1446:
Page 1447 and 1448:
SimPack/Sim++ Simulation Toolkit Si
Page 1449 and 1450:
Fire-Engine and Spare-Parts String
Page 1451 and 1452:
Geolab -- Computational Geometry Sy
Page 1453 and 1454:
Calendrical Calculations Calendrica
Page 1455 and 1456:
David Eppstein's Knuth-Morris-Pratt
Page 1457 and 1458:
Mike Trick's Graph Coloring Resourc
Page 1459 and 1460:
Frank Ruskey's Combinatorial Genera
Page 1461 and 1462:
Arrange - maintainance of arrangeme
Page 1463 and 1464:
LP_SOLVE: Linear Programming Code L
Page 1465 and 1466:
PARI - Package for Number Theory Se
Page 1467 and 1468:
TSP solvers TSP solvers tsp-solve i
Page 1469 and 1470:
PHYLIP -- inferring phylogenic tree
Page 1471 and 1472:
Skeletonization Software (2-D) Skel
Page 1473 and 1474:
agrep - Approximate General Regular
Page 1475 and 1476:
CAP -- Contig Assembly Program CAP
Page 1477 and 1478:
NAUTY -- Graph Isomorphism NAUTY --
Page 1479 and 1480:
BIPM -- Bipartite Matching Codes BI
Page 1481 and 1482:
LAPACK and LINPACK -- Linear Algebr
Page 1483 and 1484:
User Comments User Comments Archive
Page 1485 and 1486:
The Algorithm Design Manual Most pr
Page 1487 and 1488:
The Algorithm Design Manual 5.6 War
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