导语

  

内容提要

  

    开发健壮的软件需要高效的算法，但是程序员们很少能够理解可用方案的适用范围。乔治·T·海涅曼、加里·波利斯、斯坦利·塞克欧著的《算法技术手册（影印版第2版）（英文版）》讲解了各种可用于解决各种编码问题的现有算法，可以帮助你作出正确的选择和实现——只需要一般程度的数学知识就足以使你理解并分析算法的性能。
    较之理论而言，本书专注于应用。书中本着严谨细致的原则，提供了用法说明以及由多种语言实现的真实代码。这一版的更新内容包括一些新算法的Python实现、维诺图的实现以及有关空间树结构的全新章节，比如R树和四叉树。

Preface to the Second Edition
1. Thinking in Algorithms
  Understand the Problem
  Naive Solution
  Intelligent Approaches
  Summary
  References
2. The Mathematics of Algorithms
  Size of a Problem Instance
  Rate of Growth of Functions
  Analysis in the Best, Average, and Worst Cases
  Performance Families
  Benchmark Operations
  References
3. Algorithm Building Blocks
  Algorithm Template Format
  Pseudocode Template Format
  Empirical Evaluation Format
  Floating-Point Computation
  Example Algorithm
  Common Approaches
  References
4. Sorting Algorithms
  Transposition Sorting
  Selection Sort
  Heap Sort
  Partition-Based Sorting
  Sorting without Comparisons
  Bucket Sort
  Sorting with Extra Storage
  String Benchmark Results
  Analysis Techniques
  References
5. Searching
  Sequential Search
  Binary Search
  Hash-Based Search
  Bloom Filter
  Binary Search Tree
  References
6. Graph Algorithms
  Graphs
  Depth-First Search
  Breadth-First Search
  Single-Source Shortest Path
  Dijkstra's Algorithm for Dense Graphs
  Comparing Single-Source Shortest-Path Options
  All-Pairs Shortest Path
  Minimum Spanning Tree Algorithms
  Final Thoughts on Graphs
  References
7. Path Finding in AI
  Game Trees
  Path-Finding Concepts
  Minimax
  NegMax
  AlphaBeta
  Search Trees
  Depth-First Search
  Breadth-First Search
  A'Search
  Comparing Search-Tree Algorithms
  References
8. Network Flow Algorithms
  Network Flow
  Maximum Flow
  Bipartite Matching
  Reflections on Augmenting Paths
  Minimum Cost Flow
  Transshipment
  Transportation
  Assignment
  Linear Programming
  References
9. Computational Ge0metry
  Classifying Problems
  Convex Hull
  Convex Hull Scan
  Computing Line-Segment Intersections
  LineSweep
  Voronoi Diagram
  References
10. Spatial Tree Structures
  Nearest Neighbor Queries
  Range Queries
  Intersection Queries
  Spatial Tree Structures
  Nearest Neighbor Queries
  Range Query
  Quadtrees
  R-Trees
  References
11. Emerging Algorithm Categories
  Variations on a Theme
  Approximation Algorithms
  Parallel Algorithms
  Probabilistic Algorithms
  References
12. Epilogue: Principles of Algorithms
  Know Your Data
  Decompose a Problem into Smaller Problems
  Choose the Right Data Structure
  Make the Space versus Time Trade-Off
  Construct a Search
  Reduce Your Problem to Another Problem
  Writing Algorithms Is Hard-Testing Algorithms Is Harder
  Accept Approximate Solutions When Possible
  Add Parallelism to Increase Performance
A. Benchmarking
Index