About the Book

The Stony Brook Algorithm Repository

Steven Skiena
Stony Brook University
Dept. of Computer Science

• By Language
  • C
  • C++
  • C#
  • Java
  • FORTRAN
  • Python
  • Mathematica
  • Pascal
  • ADA
  • Lisp
  • Binary
• By Problem
  • 1.1 Data Structures
    • Dictionaries
    • Priority Queues
    • Suffix Trees and Arrays
    • Graph Data Structures
    • Set Data Structures
    • Kd-Trees
  • 1.2 Numerical Problems
    • Solving Linear Equations
    • Bandwidth Reduction
    • Matrix Multiplication
    • Determinants and Permanents
    • Constrained and Unconstrained Optimization
    • Linear Programming
    • Random Number Generation
    • Factoring and Primality Testing
    • Arbitrary Precision Arithmetic
    • Knapsack Problem
    • Discrete Fourier Transform
  • 1.3 Combinatorial Problems
    • Sorting
    • Searching
    • Median and Selection
    • Generating Permutations
    • Generating Subsets
    • Generating Partitions
    • Generating Graphs
    • Calendrical Calculations
    • Job Scheduling
    • Satisfiability
  • 1.4 Graph Problems -- polynomial-time problems
    • Connected Components
    • Topological Sorting
    • Minimum Spanning Tree
    • Shortest Path
    • Transitive Closure and Reduction
    • Matching
    • Eulerian Cycle / Chinese Postman
    • Edge and Vertex Connectivity
    • Network Flow
    • Drawing Graphs Nicely
    • Drawing Trees
    • Planarity Detection and Embedding
  • 1.5 Graph Problems -- hard problems
    • Clique
    • Independent Set
    • Vertex Cover
    • Traveling Salesman Problem
    • Hamiltonian Cycle
    • Graph Partition
    • Vertex Coloring
    • Edge Coloring
    • Graph Isomorphism
    • Steiner Tree
    • Feedback Edge/Vertex Set
  • 1.6 Computational Geometry
    • Robust Geometric Primitives
    • Convex Hull
    • Triangulation
    • Voronoi Diagrams
    • Nearest Neighbor Search
    • Range Search
    • Point Location
    • Intersection Detection
    • Bin Packing
    • Medial-Axis Transformation
    • Polygon Partitioning
    • Simplifying Polygons
    • Shape Similarity
    • Motion Planning
    • Maintaining Line Arrangements
    • Minkowski Sum
  • 1.7 Set and String Problems
    • Set Cover
    • Set Packing
    • String Matching
    • Approximate String Matching
    • Text Compression
    • Cryptography
    • Finite State Machine Minimization
    • Longest Common Substring
    • Shortest Common Superstring
• Algorithm Links
  • Algorithm Lectures
  • Algorithm Design Manual Information
  • CSE 373 Course page
  • NIST Dictory of Algorithms and Data Structures
  • World of Mathematics
  • Programming Challenges
  • Graduate Study Opportuinties

1. Many different NP problems such as Hamiltonian Cycle Promlem, Extended 15-Puzzle, Hanoi Towers Puzzle, Blocksworld problem and others can be reduced to SAT01 very easily and the new introduced SAT01 variables have natural meanings at that.

2. The powerful propogation method for SAT01 is considered to perform its reduction and to recognize hidden binary relatins among variables.

This site contains a solver for SAT01 and Qualex -- a weighted clique solver new release of the maximum-weight clique problem solver QUALEX (ver. 1.1) is available now at my NP-Completeness Page:

http://www.busygin.dp.ua/npc.html http://www.geocities.com/st_busygin/ (mirror)

It is a very efficient solver usually able to find an exact solution within O(Nr_vert^3) time. See its results on DIMACS clique instances:

http://www.busygin.dp.ua/dimacs_clique.html http://www.geocities.com/st_busygin/dimacs_clique.html (mirror)