Lecture Notes On Design And Analysis Of Algorithms

Lecture Notes on Design and Analysis of Algorithms

These ecture notes give a comprehensive introduction to the basic techniques in the design and analysis of algorithms. It covers major methodologies, including greedy methods, which build up solutions piece by piece; dynamic programming (DP), which breaks down problems into simpler subproblems, solves them, and memorizes their solutions; and backtracking, which incrementally generates candidates for solutions and discards those that cannot satisfy criteria. It also discusses the method of Branch and Bound, where all branches on a solution space are systematically explored until the best possible solution is obtained. These methods are crucial in the design of nice algorithms with a view to efficiency, and they form the basis of complex computational problems that require solutions.

Author(s): Annamalai University

96 Pages

Advanced Algorithms by BMS College of Engineering

This PDF deals with some advanced topics in the design of algorithms, focusing on Dynamic Programming. The application domains of DP are discussed and cover classic problems, including Matrix Chain Multiplication, that is, finding an optimal order to multiply many matrices, and Rod Cutting, which is just a typical 4-inch rod problem. Its notes include insights into the steps of DP, its recursive tree structures, and problem-solving through the bottom-up approach. The wide de-balcony of these topics helps the reader understand how DP can be applied to a variety of optimization problems and demonstrates both theoretical and practical aspects of algorithm design.

Author(s): BMS College of Engineering

152 Pages

Advanced Algorithms by Anupam Gupta

These all are very extensive notes on fairly advanced topics in algorithms—both theoretical and practical. Here we deal with discrete algorithms for minimum spanning trees, arborescences (directed spanning trees), dynamic algorithms for problems in graph connectivity, and the shortest path. Other topics discussed in the paper are the combinatorial, algebraic algorithms for graph matching techniques and their corresponding challenges developed within high-dimensional spaces via the technique of dimension reduction and streaming algorithms. Other topics but not triangulated within include the approximate max-flows, online learning, and interior-point methods. The notes thus present a framework in its totality for learning and analyzing super advanced algorithms and thus become a good source to glean insights for an ocean of problems in computer science.

Author(s): Anupam Gupta

309 Pages

Lecture Notes On Design And Analysis Of Algorithms

Lecture Notes on Design and Analysis of Algorithms by Mr. S.K. Sathua, Dr. M.R. Kabat, and Dr. R. Mohanty, published November 14, 2020, is an 80-page document that provides a vital summary of some of the significant notions of algorithms. It first of all provides the basics of the growth of functions and recurrences, while techniques for the solution of these recurrences include substitution and recursion trees. These notes introduce the Master Method for analyzing divide and conquer algorithms and provide worst-case analysis of merge sort, quick sort, and binary search. Other topics it covers are heaps, heap sort, priority queues, and sorting lower bounds, thus proving very valuable for comprehending core principles in algorithm analysis and design.

Author(s): Mr. S.K. Sathua, Dr. M.R. Kabat and Dr. R. Mohanty

80 Pages

Data Structures And Algorithms by Sugih Jamin

The book Data Structures and Algorithms by Sugih Jamin covers all the basic concepts of Computer Science in a very balanced way. It involves topics such as linked lists, stacks, and queues to more advanced topics such as binary search trees, heaps, and balanced search trees. Jama's text emphasizes an implementation perspective and algorithmic patterns, which will facilitate a more effective way of understanding and applying the concepts presented. This book will be very useful for the students and professionals who want to establish a sound foundation in data structures and algorithms by providing a solid theoretical background supported by practical examples that explain how problems are solved.

Author(s): Sugih Jamin

NA Pages

Advanced Algorithms Lectures by Shuchi Chawla

Advanced Algorithms Lectures by Shuchi Chawla give an insight into advanced techniques in the design and analysis of algorithms. The lectures cover topics such as greedy algorithms, dynamic programming, and network flow applications. Advanced topics, including randomized algorithms and Karger's min-cut algorithm, NP-completeness, together with linear programming, primal-dual algorithms, and semi-definite programming, are discussed. Chawla also deals with models like Probably Approximately Correct (PAC) and boosting within this framework. This set of lectures comprehensively covers advanced algorithmic methodologies along with their applications and constitutes an excellent resource for students and researchers interested in advanced classes of algorithmic techniques and their applications to pressing real-world problems.

Author(s): Shuchi Chawla

195 Pages