Algorithms: Design and Analysis

Algorithms are essential for computing theory and practice, with over 120 exercises and programming projects. Chapters cover basic knowledge of mathematics, sorting techniques, greedy approach, dynamic programming, branch and bound, backtracking, amortized analysis, order statistics, graph algorithms, BFS, DFS, spanning tree, flow maximization algorithms, shortest path algorithms, binary search tree, red black tree, binomial heap, B-Tree, and Fibonacci heap. Approximation algorithms, sorting networks, matrix operations, fast Fourier transformation, number theoretic algorithms, computational geometry, randomized algorithms, string matching, NP-Hard, NP-Completeness, and Cook's theorem are also covered.

\n Format: Paperback / softback
\n Length: 178 pages
\n Publication date: 08 March 2021
\n Publisher: De Gruyter
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Algorithms are the backbone of computing, serving as both a theoretical foundation and a practical tool. The authors of this textbook aimed to strike a balance between complexity and accessibility, creating a resource that would engage and educate students while remaining accessible to self-study. With over 120 exercises, the book offers a comprehensive exploration of the field, including drills for practice and thought-provoking questions that reinforce the material covered.

The text is organized into six chapters, covering a range of topics essential for understanding algorithms. Chapter 1 introduces basic mathematical concepts, including relations, recurrence relations, and solution techniques. Chapter 2 delves into different sorting techniques and their analysis, while Chapter 3 explores greedy approaches, dynamic programming, branch and bound techniques, backtracking, and problem-solving strategies. Chapter 4 explores graph algorithms, including Breadth First Search (BFS), Depth First Search (DFS), Spanning Tree, Flow Maximization Algorithms, and Shortest Path Algorithms. Chapter 5 introduces binary search trees, red-black trees, binomial heaps, B-trees, and Fibonacci heaps. Chapter 6 covers approximation algorithms, sorting networks, matrix operations, Fast Fourier Transformation, number theoretic algorithms, computational geometry, randomized algorithms, string matching, NP-Hardness, NP-Completeness, and Cook's theorem.

Each chapter is accompanied by detailed explanations, examples, and exercises designed to reinforce the learning process. The book also includes programming projects that allow students to apply their knowledge and develop practical skills. Whether you're a computer science student or a professional seeking to enhance your algorithm expertise, this textbook is an invaluable resource. Its comprehensive coverage, engaging exercises, and practical projects make it an essential tool for anyone looking to master the art of algorithms.

\n Weight: 320g\n
Dimension: 174 x 244 x 17 (mm)\n
ISBN-13: 9783110693416\n \n