Design and Analysis of Algorithms
Price: 980.00 INR
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ISBN:
9780198093695
Publication date:
15/12/2014
Paperback
788 pages
241.0x184.0mm
Price: 980.00 INR
We sell our titles through other companies
Disclaimer :You will be redirected to a third party website.The sole responsibility of supplies, condition of the product, availability of stock, date of delivery, mode of payment will be as promised by the said third party only. Prices and specifications may vary from the OUP India site.
ISBN:
9780198093695
Publication date:
15/12/2014
Paperback
788 pages
241.0x184.0mm
Design and Analysis of Algorithms is designed to serve as a textbook for the undergraduate students of computer science engineering and information technology as well as postgraduate students of computer applications. The book aims to empower students with in-depth knowledge of the fundamental concepts and the design, analysis, and implementation aspects of algorithms.
Suitable for: Design and Analysis of Algorithms is designed to serve as a textbook for the undergraduate students of computer science engineering and information technology as well as postgraduate students of computer applications.
Rights: World Rights
Description
Design and Analysis of Algorithms is designed to serve as a textbook for the undergraduate students of computer science engineering and information technology as well as postgraduate students of computer applications. The book aims to empower students with in-depth knowledge of the fundamental concepts and the design, analysis, and implementation aspects of algorithms. The book begins with the basics of algorithms and problem-solving concepts followed by an introduction to algorithm writing, and analysis of iterative and recursive algorithms. In-depth explanations and designing techniques of various types of algorithms used for problem-solving such as brute force technique, divide-and-conquer technique, decrease-and-conquer strategy, greedy approach, transform-and-conquer strategy, dynamic programming, branch-and-bound approach, and backtracking are provided in the book. It also covers discussion of string algorithms, iterative improvement, linear programming, computability theory, NP-hard problems, NP- completeness, randomized algorithms, approximation algorithms, and parallel algorithms. The book includes a variety of chapter-end pedagogical features such as point-wise summary, glossary, review questions, exercises, and additional problems to help readers test their understanding and also apply and practise the concepts learnt. Appendices on basic mathematics and proof techniques are given to aid students refresh the fundamental concepts.
Table of contents
Chapter 1. Introduction to Algorithms
Chapter 2. Basics of Algorithm Writing
Chapter 3. Basics of Algorithm Analysis
Chapter 4. Mathematical Analysis of Recursive Algorithms
Chapter 5. Data Structures—I
Chapter 6. Data Structures—II
Chapter 7. Brute Force Approaches
Chapter 8. Divide-and-conquer Approach
Chapter 9. Decrease-and-conquer Approach
Chapter 10. Time-Space Tradeoffs
Chapter 11. Greedy Algorithms
Chapter 12. Transform-and-conquer Approach
Chapter 13. Dynamic Programming
Chapter 14. Backtracking
Chapter 15. Branch-and-bound Technique
Chapter 16. String Algorithms
Chapter 17. Iterative Improvement and Linear Programming
Chapter 18. Basics of Computational Complexity
Chapter 19. Randomized and Approximation Algorithms
Chapter 20. Parallel Algorithms
Features
- In-depth treatment for topics such as greedy approach, dynamic programming, transform-and-conquer technique, decrease-and-conquer technique, linear programming, and randomized and approximation algorithms
- Dedicated chapters on backtracking and branch-and-bound techniques, string matching algorithms, and parallel algorithms
- Extensive discussion on the developing and designing aspects of algorithms using minimal mathematics and numerous examples
- Judicious presentation of algorithms using step-wise approach and pseudocodes throughout the text
- Historical notes on various topics and chapter-end crossword puzzles provided to engage readers and enhance their interest in the subject
- Online Resources
- For faculty:
- PowerPoint Slides
- Solutions Manual
- For students:
- Answers to the Crossword Puzzles
Description
Design and Analysis of Algorithms is designed to serve as a textbook for the undergraduate students of computer science engineering and information technology as well as postgraduate students of computer applications. The book aims to empower students with in-depth knowledge of the fundamental concepts and the design, analysis, and implementation aspects of algorithms. The book begins with the basics of algorithms and problem-solving concepts followed by an introduction to algorithm writing, and analysis of iterative and recursive algorithms. In-depth explanations and designing techniques of various types of algorithms used for problem-solving such as brute force technique, divide-and-conquer technique, decrease-and-conquer strategy, greedy approach, transform-and-conquer strategy, dynamic programming, branch-and-bound approach, and backtracking are provided in the book. It also covers discussion of string algorithms, iterative improvement, linear programming, computability theory, NP-hard problems, NP- completeness, randomized algorithms, approximation algorithms, and parallel algorithms. The book includes a variety of chapter-end pedagogical features such as point-wise summary, glossary, review questions, exercises, and additional problems to help readers test their understanding and also apply and practise the concepts learnt. Appendices on basic mathematics and proof techniques are given to aid students refresh the fundamental concepts.
Read MoreTable of contents
Chapter 1. Introduction to Algorithms
Chapter 2. Basics of Algorithm Writing
Chapter 3. Basics of Algorithm Analysis
Chapter 4. Mathematical Analysis of Recursive Algorithms
Chapter 5. Data Structures—I
Chapter 6. Data Structures—II
Chapter 7. Brute Force Approaches
Chapter 8. Divide-and-conquer Approach
Chapter 9. Decrease-and-conquer Approach
Chapter 10. Time-Space Tradeoffs
Chapter 11. Greedy Algorithms
Chapter 12. Transform-and-conquer Approach
Chapter 13. Dynamic Programming
Chapter 14. Backtracking
Chapter 15. Branch-and-bound Technique
Chapter 16. String Algorithms
Chapter 17. Iterative Improvement and Linear Programming
Chapter 18. Basics of Computational Complexity
Chapter 19. Randomized and Approximation Algorithms
Chapter 20. Parallel Algorithms
