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

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Interesting Data Files Interesting Data Files Below we point to several interesting data files. These files can be used as test data for several of the Implementation Challenges given in The Algorithm Design Manual , but are also likely to be of independent interest. ● Airplane routes and schedules (from Roberto Tamassia -- local copy) ● Name-ethnicity data; over 3000 names from several nations (local copy) About the Book Send us Mail Go to Main Page file:///E|/WEBSITE/BIBLIO/TESTDATA/DATA.HTM [19/1/2003 1:36:29]
About the Ratings About the Ratings Our implementations are classified by the problems they solve. For each problem, we rate all the implementations according to usefulness on a 1 to 10 scale, with 10 meaning the most useful and 1 least useful. The usefulness of an implementation is supposed to reflect how likely it is that someone looking for code will be happy with what they find. Our ratings are completely subjective and reflect our judgement. Please feel free to send corrections and feedback based on your experiences. Please note that many of these implementations with low usefulness ratings were produced primarily for expository purposes, and can serve as excellent models to study or emulate if not as ready-to-run code. Go to Main Page file:///E|/WEBSITE/INFO/RATINGS.HTM [19/1/2003 1:36:29]
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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:
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Introduction to Algorithms ● Reas
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Data Structures and Sorting divide-
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Breaking Problems Down ● Dynamic
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Graph Algorithms The take-home less
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Combinatorial Search and Heuristic
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Intractable Problems and Approximat
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How to Design Algorithms Next: Reso
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How to Design Algorithms with a cou
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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
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Algorithmic Resources Next: Softwar
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References L. Adleman. Algorithmic
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References AS89 Ata83 Ata84 problem
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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:
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References N. Gibbs, W. Poole, and
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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:
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Correctness and Efficiency Next: Co
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Correctness NearestNeighborTSP(P) P
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Correctness Figure: A bad example f
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Efficiency Next: Expressing Algorit
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Keeping Score Next: The RAM Model o
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The RAM Model of Computation substa
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Best, Worst, and Average-Case Compl
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The Big Oh Notation Figure: Illustr
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Logarithms Next: Modeling the Probl
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Logarithms justified in ignoring th
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Modeling the Problem Figure: Modeli
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About the War Stories Next: War Sto
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War Story: Psychic Modeling Next: E
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War Story: Psychic Modeling have pu
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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
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Containers Next: Dictionaries Up: F
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Dictionaries Next: Binary Search Tr
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Binary Search Trees BinaryTreeQuery
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Priority Queues Next: Specialized D
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Specialized Data Structures Next: S
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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
Page 173 and 174:
Exercises Next: Implementation Chal
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Exercises used to select the pivot.
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Dynamic Programming Next: Fibonacci
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Fibonacci numbers Next: The Partiti
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Fibonacci numbers Next: The Partiti
Page 183 and 184:
The Partition Problem . What is the
Page 185 and 186:
The Partition Problem Figure: Dynam
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Approximate String Matching Next: L
Page 189 and 190:
Approximate String Matching The val
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Longest Increasing Sequence Will th
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Minimum Weight Triangulation Next:
Page 195 and 196:
Limitations of Dynamic Programming
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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
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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 ,
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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
Page 249 and 250:
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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Page 267 and 268:
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
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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
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Matrix Multiplication Next: Determi
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Matrix Multiplication The linear al
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Determinants and Permanents Next: C
Page 389 and 390:
Determinants and Permanents exposit
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Constrained and Unconstrained Optim
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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
Page 401 and 402:
Random Number Generation is largely
Page 403 and 404:
Random Number Generation Related Pr
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Factoring and Primality Testing The
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Factoring and Primality Testing Alg
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Arbitrary-Precision Arithmetic If y
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Arbitrary-Precision Arithmetic PARI
Page 413 and 414:
Knapsack Problem Next: Discrete Fou
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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
Page 421 and 422:
Combinatorial Problems Next: Sortin
Page 423 and 424:
Sorting Next: Searching Up: Combina
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Sorting The simplest approach to ex
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Sorting operations, implying an sor
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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
Page 443 and 444:
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
Page 451 and 452:
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
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Job Scheduling shop scheduling incl
Page 461 and 462:
Satisfiability logic, and automatic
Page 463 and 464:
Satisfiability Next: Graph Problems
Page 465 and 466:
Graph Problems: Polynomial-Time rec
Page 467 and 468:
Connected Components Testing the co
Page 469 and 470:
Connected Components discussing gra
Page 471 and 472:
Topological Sorting contradiction t
Page 473 and 474:
Minimum Spanning Tree Next: Shortes
Page 475 and 476:
Minimum Spanning Tree help you sort
Page 477 and 478:
Shortest Path Next: Transitive Clos
Page 479 and 480:
Shortest Path easier to program tha
Page 481 and 482:
Shortest Path Related Problems: Net
Page 483 and 484:
Transitive Closure and Reduction
Page 485 and 486:
Transitive Closure and Reduction Al
Page 487 and 488:
Matching augmenting paths and stopp
Page 489 and 490:
Matching Combinatorica [Ski90] prov
Page 491 and 492:
Eulerian Cycle / Chinese Postman ar
Page 493 and 494:
Eulerian Cycle / Chinese Postman Ne
Page 495 and 496:
Edge and Vertex Connectivity Severa
Page 497 and 498:
Edge and Vertex Connectivity Next:
Page 499 and 500:
Network Flow programming model for
Page 501 and 502:
Network Flow Combinatorica [Ski90]
Page 503 and 504:
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
Page 511 and 512:
Planarity Detection and Embedding p
Page 513 and 514:
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
Page 527 and 528:
Traveling Salesman Problem Size is
Page 529 and 530:
Hamiltonian Cycle Eulerian cycle, p
Page 531 and 532:
Graph Partition Next: Vertex Colori
Page 533 and 534:
Graph Partition annealing, is almos
Page 535 and 536:
Vertex Coloring Several special cas
Page 537 and 538:
Vertex Coloring Notes: An excellent
Page 539 and 540:
Edge Coloring The minimum number of
Page 541 and 542:
Graph Isomorphism Next: Steiner Tre
Page 543 and 544:
Graph Isomorphism vertices into equ
Page 545 and 546:
Steiner Tree Next: Feedback Edge/Ve
Page 547 and 548:
Steiner Tree The worst case for a m
Page 549 and 550:
Feedback Edge/Vertex Set Next: Comp
Page 551 and 552:
Feedback Edge/Vertex Set An interes
Page 553 and 554:
Computational Geometry complete bib
Page 555 and 556:
Robust Geometric Primitives Next: C
Page 557 and 558:
Robust Geometric Primitives ● Are
Page 559 and 560:
Robust Geometric Primitives Related
Page 561 and 562:
Convex Hull ● How many dimensions
Page 563 and 564:
Convex Hull http://www.cs.att.com/n
Page 565 and 566:
Triangulation Next: Voronoi Diagram
Page 567 and 568:
Triangulation GEOMPACK is a suite o
Page 569 and 570:
Voronoi Diagrams Next: Nearest Neig
Page 571 and 572:
Voronoi Diagrams McDonald's, the ti
Page 573 and 574:
Nearest Neighbor Search Next: Range
Page 575 and 576:
Nearest Neighbor Search Implementat
Page 577 and 578:
Range Search Next: Point Location U
Page 579 and 580:
Range Search subdivisions in C++. I
Page 581 and 582:
Point Location the n edges for inte
Page 583 and 584:
Point Location More recently, there
Page 585 and 586:
Intersection Detection ● Do you w
Page 587 and 588:
Intersection Detection Implementati
Page 589 and 590:
Bin Packing Next: Medial-Axis Trans
Page 591 and 592:
Bin Packing approach for general sh
Page 593 and 594:
Medial-Axis Transformation Next: Po
Page 595 and 596:
Medial-Axis Transformation Implemen
Page 597 and 598:
Polygon Partitioning number of piec
Page 599 and 600:
Simplifying Polygons Next: Shape Si
Page 601 and 602:
Simplifying Polygons vertices and o
Page 603 and 604:
Shape Similarity Next: Motion Plann
Page 605 and 606:
Shape Similarity or how close it is
Page 607 and 608:
Motion Planning There is a wide ran
Page 609 and 610:
Motion Planning often arise in the
Page 611 and 612:
Maintaining Line Arrangements Think
Page 613 and 614:
Maintaining Line Arrangements Next:
Page 615 and 616:
Minkowski Sum where x+y is the vect
Page 617 and 618:
Set and String Problems Next: Set C
Page 619 and 620:
Set Cover Next: Set Packing Up: Set
Page 621 and 622:
Set Cover Figure: Hitting set is du
Page 623 and 624:
Set Packing Next: String Matching U
Page 625 and 626:
Set Packing Notes: An excellent exp
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String Matching shouldn't try. Furt
Page 629 and 630:
String Matching and texts, I recomm
Page 631 and 632:
Approximate String Matching This sa
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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
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Index (complete) normal distributio
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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
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Lecture 4 - heapsort Note iteration
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Lecture 4 - heapsort The convex hul
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Lecture 4 - heapsort 1. All leaves
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Lecture 4 - heapsort left = 2i righ
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Lecture 4 - heapsort Since this sum
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Lecture 4 - heapsort Selection sort
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Lecture 4 - heapsort Greedy Algorit
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Lecture 5 - quicksort Partitioning
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Lecture 5 - quicksort Listen To Par
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Lecture 5 - quicksort Listen To Par
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Lecture 5 - quicksort The worst cas
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Lecture 5 - quicksort Mon Jun 2 09:
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Lecture 6 - linear sorting Since 2i
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Lecture 6 - linear sorting With uni
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Lecture 6 - linear sorting Listen T
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Lecture 7 - elementary data structu
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Lecture 8 - binary trees - Joyce Ki
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Lecture 8 - binary trees TREE-MINIM
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Lecture 8 - binary trees Inorder-Tr
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Lecture 8 - binary trees Listen To
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Lecture 8 - binary trees insert(b)
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Lecture 8 - binary trees Not (1) -
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Lecture 9 - catch up Next: Lecture
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Lecture 10 - tree restructuring 1.
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Lecture 10 - tree restructuring Lis
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Lecture 10 - tree restructuring Not
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Lecture 10 - tree restructuring Cas
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Lecture 11 - backtracking Next: Lec
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Lecture 11 - backtracking Only 63 s
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Lecture 11 - backtracking Recursion
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Lecture 11 - backtracking Specifica
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Lecture 12 - introduction to dynami
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Lecture 13 - dynamic programming ap
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Lecture 14 - data structures for gr
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Lecture 15 - DFS and BFS Next: Lect
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Lecture 15 - DFS and BFS In a DFS o
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Lecture 15 - DFS and BFS It could u
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Lecture 15 - DFS and BFS Algorithm
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Lecture 16 - applications of DFS an
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Lecture 17 - minimum spanning trees
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Lecture 18 - shortest path algorthm
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Lecture 19 - satisfiability Next: L
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Lecture 19 - satisfiability Why? Th
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Lecture 19 - satisfiability between
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Lecture 19 - satisfiability Note th
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Lecture 20 - integer programming Ex
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Lecture 20 - integer programming Ne
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Lecture 21 - vertex cover Proof: VC
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Lecture 21 - vertex cover Question:
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Lecture 21 - vertex cover seen to d
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Lecture 22 - techniques for proving
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Lecture 22 - techniques for proving
Page 1031 and 1032: Lecture 22 - techniques for proving
Page 1033 and 1034: Lecture 22 - techniques for proving
Page 1035 and 1036: Lecture 23 - approximation algorith
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 1081: Visual Links Index file:///E|/WEBSI
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
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Genocop -- Optimization via Genetic
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1.2.6 Linear Programming ● Knapsa
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1.2.7 Random Number Generation ●
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1.3.10 Satisfiability ● Constrain
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Qhull - higher dimensional convex h
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1.6.5 Nearest Neighbor Search 1.6.5
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1.6.7 Point Location 1.6.7 Point Lo
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1.6.10 Medial-Axis Transformation 1
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1.6.3 Triangulation 1.6.3 Triangula
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Nijenhuis and Wilf: Combinatorial A
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1.5.5 Hamiltonian Cycle 1.5.5 Hamil
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1.4.6 Matching 1.4.6 Matching INPUT
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A compendium of NP optimization pro
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1.6.9 Bin Packing 1.6.9 Bin Packing
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1.6.12 Simplifying Polygons 1.6.12
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1.6.13 Shape Similarity 1.6.13 Shap
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1.6.11 Polygon Partitioning 1.6.11
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1.4.3 Minimum Spanning Tree 1.4.3 M
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1.6.15 Maintaining Line Arrangement
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1.3.7 Generating Graphs 1.3.7 Gener
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1.2.11 Discrete Fourier Transform 1
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1.5.8 Edge Coloring 1.5.8 Edge Colo
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1.3.3 Median and Selection 1.3.3 Me
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1.3.1 Sorting 1.3.1 Sorting INPUT O
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Plugins for use with the CDROM Plug
Page 1187 and 1188:
Implementation Challenges Next: Dat
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Implementation Challenges Next: Gra
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Implementation Challenges Next: Int
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Caveats Next: Data Structures Up: A
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1.1.1 Dictionaries ● Priority Que
Page 1197 and 1198:
1.1.4 Graph Data Structures ● Gra
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1.1.5 Set Data Structures ● Gener
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1.2.1 Solving Linear Equations ●
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1.2.2 Bandwidth Reduction ● Topol
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1.2.4 Determinants and Permanents
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1.2.8 Factoring and Primality Testi
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1.2.9 Arbitrary Precision Arithmeti
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1.2.10 Knapsack Problem ● Linear
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1.3.2 Searching ● Sorting Go to t
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1.3.4 Generating Permutations ● C
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1.3.5 Generating Subsets ● Genera
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1.3.6 Generating Partitions ● Gen
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1.3.8 Calendrical Calculations Go t
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1.3.9 Job Scheduling ● Feedback E
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1.4.2 Topological Sorting Related P
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1.4.8 Edge and Vertex Connectivity
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1.4.10 Drawing Graphs Nicely ● Pl
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1.4.11 Drawing Trees ● Planarity
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1.4.12 Planarity Detection and Embe
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1.5.2 Independent Set ● Vertex Co
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1.5.3 Vertex Cover ● Independent
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1.5.4 Traveling Salesman Problem
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1.5.6 Graph Partition ● Network F
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1.5.7 Vertex Coloring Related Probl
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1.5.11 Feedback Edge/Vertex Set Go
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1.6.1 Robust Geometric Primitives G
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1.6.6 Range Search ● Kd-Trees ●
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1.6.8 Intersection Detection ● Ro
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1.6.16 Minkowski Sum Go to the corr
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1.7.1 Set Cover ● Set Packing ●
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1.7.2 Set Packing Go to the corresp
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1.7.3 String Matching ● Approxima
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1.7.4 Approximate String Matching
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1.7.5 Text Compression Go to the co
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1.7.6 Cryptography ● Text Compres
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1.7.7 Finite State Machine Minimiza
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1.7.8 Longest Common Substring ●
Page 1271 and 1272:
1.7.9 Shortest Common Superstring G
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Handbook of Algorithms and Data Str
Page 1275 and 1276:
Moret and Shapiro's Algorithms P to
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Index B Up: Index - All Index: B ba
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Index C Up: Index - All Index: C ch
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Index E Up: Index - All Index: E ed
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Index G Up: Index - All Index: G ga
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Index I Up: Index - All Index: I in
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Index L Up: Index - All Index: L li
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Index N Up: Index - All Index: N ne
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Index P Up: Index - All Index: P pa
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Index R Up: Index - All Index: R RA
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Index S successor supercomputer , s
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Index U Up: Index - All Index: U un
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Index W Up: Index - All Index: W wo
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Index (complete) bin packing bipart
Page 1303 and 1304:
Index (complete) Fourier transform
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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/
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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
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The Algorithm Design Manual Most pr
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The Algorithm Design Manual 5.6 War
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