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

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The Algorithm Design Manual The Algorithm Design Manual ● Overview ● Contents ● About the Author ● To Order Author Steven S. Skiena Department of Computer Science State University of New York at Stony Brook Overview http://www.telospub.com/catalog/COMPUTERSCI/Algorithm.html (1 of 5) [19/1/2003 2:00:54]
The Algorithm Design Manual Most professional programmers are not well equipped to tackle algorithm design problems. "The Algorithm Design Manual" by Steve Skiena of SUNY Stony Brook, is uniquely designed to provide access to combinatorial algorithms technology for computer professionals and students. Skiena has taken some of the "mystery" out of finding the right algorithm for the job, by drawing heavily on the author's own real-world experiences. Thus the work takes on a very practical character, as reflected in its title: "Manual". The Book is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, comprising the catalog of algorithmic resources, implementations, and an extensive bibliography. The primary audience for this book/CD-ROM combination is the working professional who uses algorithms on a regular or occasional basis and has need for a handy reference. A major feature of this book is the inclusion of a complete "catalog" of important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. Nothing like this catalog exists in the computing literature for general computer algorithms. This work can also readily be used as a textbook or course supplement in standard courses on algorithm design. Pedagogic features include pen-and paper exercises, "team projects", independent student projects, "take home" lessons (goals) at the beginning of chapters. Other teaching and learning aids reside on the accompanying CD-ROM. The multiplatiform CD-ROM contains a full hypertext version of the book, with a comprehensive online index, and all of the code/algorithms residing on the author's web site at Stony Brook in the "Algorithm Repository" there: www.cs.sunysb.edu/~algorith/. URLs for all cited implementations mirroring the Stony Brook web site and algorthim repository are included. Also included on the CD-ROM are 10 hours of audio lectures presented by the author, and series of slides which instructors can use to help teach their courses. There is additional useful information and updates which are available through accessing the author's web site. Table of Contents Part I Techniques Chapter 1 Introduction to Algorithms 1.1 Correctness and Efficiency 1.2 Expressing Algorithms 1.3 Keeping Score http://www.telospub.com/catalog/COMPUTERSCI/Algorithm.html (2 of 5) [19/1/2003 2:00:54]
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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
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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
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The Partition Problem . What is the
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The Partition Problem Figure: Dynam
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Approximate String Matching Next: L
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Approximate String Matching The val
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Longest Increasing Sequence Will th
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Minimum Weight Triangulation Next:
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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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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
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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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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:
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Solving Linear Equations algorithm
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Solving Linear Equations Matrix inv
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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
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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
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Random Number Generation is largely
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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
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Knapsack Problem Next: Discrete Fou
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Knapsack Problem is a subset of S'
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Discrete Fourier Transform Next: Co
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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
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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
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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
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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
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Connected Components Testing the co
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Connected Components discussing gra
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Topological Sorting contradiction t
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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
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Network Flow Combinatorica [Ski90]
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Drawing Graphs Nicely vertices are
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Drawing Graphs Nicely labs.com/orgs
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Drawing Trees such as the map of th
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Planarity Detection and Embedding N
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Planarity Detection and Embedding p
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Graph Problems: Hard Problems ● C
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Clique approximate even to within a
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Independent Set Next: Vertex Cover
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Independent Set Related Problems: C
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Vertex Cover Vertex cover and indep
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Traveling Salesman Problem Next: Ha
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Traveling Salesman Problem practice
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Traveling Salesman Problem Size is
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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
Page 579 and 580:
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
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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
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Approximate String Matching This sa
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Approximate String Matching http://
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Text Compression Next: Cryptography
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Text Compression code string. ASCII
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Cryptography Next: Finite State Mac
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Cryptography ● How can I validate
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Cryptography MD5 [Riv92] is the sec
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Finite State Machine Minimization F
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Finite State Machine Minimization S
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Longest Common Substring than edit
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Longest Common Substring include [A
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Shortest Common Superstring Finding
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Software systems Next: LEDA Up: Alg
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LEDA Next: Netlib Up: Software syst
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Netlib Algorithms Mon Jun 2 23:33:5
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The Stanford GraphBase Next: Combin
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Algorithm Animations with XTango Ne
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Programs from Books Next: Discrete
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Handbook of Data Structures and Alg
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Algorithms from P to NP Next: Compu
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Algorithms in C++ Next: Data Source
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Textbooks Next: On-Line Resources U
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On-Line Resources Next: Literature
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People Next: Software Up: On-Line R
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Professional Consulting Services Ne
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Index A Up: Index - All Index: A ab
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Index A artists steal ASA ASCII asp
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Index B binary representation - sub
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Index C Up: Index - All Index: C C+
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Index C clustering , , co-NP coding
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Index C consulting services , conta
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Index D Up: Index - All Index: D DA
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Index D Dictionaries dictionaries -
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Index D dynamic programming - appli
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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-
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Index G geometric shortest path , g
Page 707 and 708:
Index H Up: Index - All Index: H ha
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Index H Algorithms Tue Jun 3 11:59:
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Index I independent set - alternate
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Index J Up: Index - All Index: J ji
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Index K Algorithms Tue Jun 3 11:59:
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Index L linear congruential generat
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Index M Up: Index - All Index: M ma
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Index M mindset minima minimax sear
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Index N Up: Index - All Index: N na
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Index N numerical analysis numerica
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Index O overlap graph overpasses -
Page 729 and 730:
Index P , , , , , , , , , , passwor
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Index P polygons polygon triangulat
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Index Q Up: Index - All Index: Q Qh
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Index R ranking combinatorial objec
Page 737 and 738:
Index S Up: Index - All Index: S s-
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Index S Shape Similarity shape simp
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Index S solar year Solving Linear E
Page 743 and 744:
Index S straight-line graph drawing
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Index T Up: Index - All Index: T ta
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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
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Index Y Up: Index - All Index: Y Yo
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Index (complete) Up: Index - All In
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Index (complete) arm, robot around
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Index (complete) binary search tree
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Index (complete) center vertex, , C
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Index (complete) compaction compari
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Index (complete) counting paths, co
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Index (complete) deletion from bina
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Index (complete) dominance ordering
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Index (complete) English to French
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Index (complete) file directory tre
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Index (complete) geom.bib, geometri
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Index (complete) Hamiltonian Cycle
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Index (complete) implementation cha
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Index (complete) job-shop schedulin
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Index (complete) linear programming
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Index (complete) , , , , , , , math
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Index (complete) modular arithmetic
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Index (complete) normal distributio
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Index (complete) parallel algorithm
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Index (complete) planar subdivision
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Index (complete) proof of correctne
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Index (complete) regular expression
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Index (complete) self-organizing tr
Page 801 and 802:
Index (complete) sine functions sin
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Index (complete) spring embedding h
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Index (complete) Symbol Technologie
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Index (complete) trial division Tri
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Index (complete) VLSI circuit layou
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1.4.4 Shortest Path 1.4.4 Shortest
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1.2.5 Constrained and Unconstrained
Page 815 and 816:
1.6.4 Voronoi Diagrams 1.6.4 Vorono
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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
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CD-ROM Installation install a sound
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Thanks! Frank Ruscica file:///E|/WE
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Thanks! Zhong Li Thanks also to Fil
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CD-ROM Installation To use the CD-R
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Binary Search in Action Binary Sear
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Binary Search in Action file:///E|/
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Binary Search in Action file:///E|/
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Postscript version of the lecture n
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Lecture 1 - analyzing algorithms Ne
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Lecture 1 - analyzing algorithms Yo
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Lecture 1 - analyzing algorithms Th
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Lecture 1 - analyzing algorithms Th
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Lecture 1 - analyzing algorithms is
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Lecture 2 - asymptotic notation How
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Lecture 2 - asymptotic notation Not
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Lecture 2 - asymptotic notation alg
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Lecture 2 - asymptotic notation Sup
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Lecture 2 - asymptotic notation Nex
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Lecture 3 - recurrence relations Is
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Lecture 3 - recurrence relations
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Lecture 3 - recurrence relations Li
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Lecture 3 - recurrence relations Su
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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 23 - approximation algorith
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About this document ... Up: No Titl
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1.1.6 Kd-Trees ● Point Location
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1.1.3 Suffix Trees and Arrays Send
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1.5.1 Clique ● Vertex Cover Go to
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1.6.2 Convex Hull Related Problems
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Visual Links Index file:///E|/WEBSI
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About the Ratings About the Ratings
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1.2 Numerical Problems 1.2 Numerica
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1.4 Graph Problems -- polynomial-ti
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1.6 Computational Geometry 1.6 Comp
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C++ Language Implementations Algori
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C Language Implementations ● POSI
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FORTRAN Language Implementations Al
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Lisp Language Implementations Algor
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Algorithm Repository -- Citations C
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Practical Algorithm Design -- User
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LEDA - A Library of Efficient Data
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Discrete Optimization Methods Discr
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Netlib / TOMS -- Collected Algorith
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Netlib / TOMS -- Collected Algorith
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Xtango and Polka Algorithm Animatio
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Combinatorica Combinatorica Combina
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file:///E|/WEBSITE/IMPLEMEN/GRAPHBA
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1.4.1 Connected Components 1.4.1 Co
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1.5.9 Graph Isomorphism 1.5.9 Graph
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1.2.3 Matrix Multiplication 1.2.3 M
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1.6.14 Motion Planning 1.6.14 Motio
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1.4.9 Network Flow 1.4.9 Network Fl
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1.1.2 Priority Queues 1.1.2 Priorit
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1.5.10 Steiner Tree 1.5.10 Steiner
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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
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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
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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 ●
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1.7.9 Shortest Common Superstring G
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Handbook of Algorithms and Data Str
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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
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Index (complete) Fourier transform
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Index (complete) parenthesization p
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Index (complete) symmetry, exploiti
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Ranger - Nearest Neighbor Search in
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DIMACS Implementation Challenges Pe
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Stony Brook Project Implementations
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Clarkson's higher dimensional conve
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file:///E|/WEBSITE/BIBLIO/TESTDATA/
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Page 1433 and 1434: file:///E|/WEBSITE/BIBLIO/TESTDATA/
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: User Comments User Comments Archive
Page 1487 and 1488: The Algorithm Design Manual 5.6 War
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