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- Numerous algorithm traces throughout the book.
- Over 1,000 end-of-section exercises—With answers to 1/3 of them in the back of the book.
- More applications than other algorithms texts.
- Elaborate world wide web site—With up-to-date support for book. An icon occurs throughout the book to indicate more explanations and examples available on the web.
- Upper bounds for worst-case times proven sharp.
- Lower bounds integrated into sections that discuss problems—e.g. after presentation of several sorting algorithms, text discusses lower bound for comparison-based sorting.
- Methods used to solve NP-complete problems—Including approximation, brute force, parameterized complexity, and heuristics.
- Recent results—Such as Pearson's polynomial-time algorithm for the coin-changing problem and parameterized complexity.
- Figures and tables illustrate concepts—Figure captions provide additional explanations and insight.
- Copyright 2004
- Dimensions: 8" x 10"
- Pages: 768
- Edition: 1st
- ISBN-10: 0-02-360692-4
- ISBN-13: 978-0-02-360692-2
Algorithms is written for an introductory upper-level undergraduate or graduate course in algorithms. With/their many years of experience in teaching algorithms courses, Richard Johnsonbaugh and Marcus Schaefer include applications of algorithms, examples, end-of-section exercises, end-of-chapter exercises, solutions to selected exercises, and notes to help the reader understand and master algorithms. Key Features
- Links theory to real-world applications such as data compression, region-finding in digital pictures, cellular phone networks, and the implementation of agrep.
- Includes five chapters that emphasize design techniques: searching (including backtracking), divide and conquer, sorting, selection, the greedy method, and dynamic programming.
- Covers distributed algorithmsa topic recommended by the ACM (2001 report) for an undergraduate curriculum.
- Features a collection of techniques, including approximation, parameterization (a recent area of research), and use of heuristics, to deal with NP-complete problems.
- Contains more than 1450 carefully developed and classroom-tested exercises, from routine to challenging. About one-third of the end-of-section exercises include solutions.
- Provides a robust Companion Website that supplements the text by providing algorithm simulation software, PowerPoint® slides, late breaking news about algorithms, references about the book's topics, computer programs, and more.
- Includes more than 300 worked examples, which provide motivation, clarify concepts, and show how to develop algorithms, demonstrate applications of the theory, and elucidate proofs.
Table of Contents
1. Mathematical Prerequisites.
2. Data Structures.
3. Searching Techniques.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
Solutions to Selected Exercises.
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