Название: A Guide to Design and Analysis of Algorithms
Автор: Soubhik Chakraborty, Prashant Pranav, Naghma Khatoon
Издательство: Nova Science Publishers, Inc.
Серия: Computer Science, Technology and Applications
Год: 2023
Страниц: 126
Язык: английский
Формат: pdf (true)
Размер: 12.6 MB

As there can be more than one algorithm for the same problem, designing and analyzing an algorithm becomes important in order to make it as efficient and robust as possible. This book will serve as a guide to design and analysis of computer algorithms. Chapter One provides an overview of different algorithm design techniques and the various applications of such techniques. Chapter Two reviews the divide and conquer strategy and the algorithm types that employ it. Chapter Three explores greedy algorithms and some problems that can be solved with this approach. Chapter Four discusses in depth the dynamic programming approach. Chapter Five provides a solution to the N-Queens problem utilizing a backtracking approach. Chapter Six elucidates the reader to branch and bound techniques and provides three solutions to problems implementing them. Part II of this book begins with Chapter Seven, where two different approaches to the analysis of algorithms are discussed. Chapter Eight reviews randomized algorithms through an empirical lens. Chapter Nine discusses Master Theorem and the many kinds of problems this Theorem can solve. Chapter Ten, the final chapter, provides notes on the empirical complexity analysis of algorithms.

An algorithm is a sequence of instructions that execute program, data processing and automated reasoning in order to solve a problem. An algorithm design is an efficient method that can we expressed in a finite amount of space and time. Different approaches can be used to solve a problem. In terms of memory, some of them can be efficient, whereas with respect to time some other approaches can be efficient. However, it is important to note that memory usage and time consumption cannot be optimized at the same time. More memory required if user need an algorithm to run in less time and if user need an algorithm to run faster than less memory required.

A brute force approach is a method for solving a problem by finding all possible option available to find a suitable solution to a given problem. The brute force method explores every possibility until a satisfactory solution is not found. For problem-solving, brute-force algorithms rely mostly on sheer computing power. Example of Brute Force algorithms are: Sequential search, Breadth-First search, Depth-First search, Bubble sort, Selection sort, Convex-Hull problem, Closest-Pair problem, and many more.

Contents:
Preface
Chapter 1 Introduction to the Design of Algorithms
Chapter 2 Divide and Conquer
Chapter 3 Greedy Algorithms
Chapter 4 Dynamic Programming
Chapter 5 Backtracking
Chapter 6 Branch and Bound
Chapter 7 Introduction to the Analysis of Algorithms
Chapter 8 Randomized Algorithms
Chapter 9 Master Theorem
Chapter 10 A Note on Empirical Complexity Analysis
References
About the Authors
Index