# JNTUH B.TECH R18 4-1 Syllabus For Advanced algorithms PDF 2022

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You will be able to find information about Advanced algorithms along with its Course Objectives and Course outcomes and also a list of textbook and reference books in this blog.You will get to learn a lot of new stuff and resolve a lot of questions you may have regarding Advanced algorithms after reading this blog. Advanced algorithms has 5 units altogether and you will be able to find notes for every unit on the CynoHub app. Advanced algorithms can be learnt easily as long as you have a well planned study schedule and practice all the previous question papers, which are also available on the CynoHub app.

All of the Topic and subtopics related to Advanced algorithms are mentioned below in detail. If you are having a hard time understanding Advanced algorithms or any other Engineering Subject of any semester or year then please watch the video lectures on the official CynoHub app as it has detailed explanations of each and every topic making your engineering experience easy and fun.

#### UNIT – I

Introduction: Role of Algorithms in computing, Order Notation, Recurrences, Probabilistic Analysis and Randomized Algorithms. Sorting and Order Statistics: Heap sort, Quick sort and Sorting in Linear Time.
Advanced Design and Analysis Techniques: Dynamic Programming- Matrix chain Multiplication, Longest common Subsequence and optimal binary Search trees.

#### UNIT – II

Greedy Algorithms – Huffman Codes, Activity Selection Problem. Amortized Analysis.
Graph Algorithms: Topological Sorting, Minimum Spanning trees, Single Source Shortest Paths, Maximum Flow algorithms.

### Get Complete Lecture Notes for Advanced algorithms on Cynohub APP

#### UNIT – III

Sorting Networks: Comparison Networks, Zero-one principle, bitonic Sorting Networks, Merging Network, Sorting Network.
Matrix Operations- Strassen’s Matrix Multiplication, Inverting matrices, Solving system of linear Equations

#### UNIT – IV

String Matching: Naive String Matching, Rabin-Karp algorithm, matching with finite Automata, Knuth- Morris – Pratt algorithm.

#### UNIT- V

NP-Completeness and Approximation Algorithms: Polynomial time, polynomial time verification, NP-Completeness and reducibility, NP-Complete problems. Approximation Algorithms- Vertex cover Problem, Travelling Sales person problem

Introduces the recurrence relations for analyzing the algorithms
Introduces the graphs and their traversals.
Describes major algorithmic techniques (divide-and-conquer, greedy, dynamic programming, Brute Force, Transform and Conquer approaches) and mention problems for which each technique is appropriate;
Describes how to evaluate and compare different algorithms using worst-case, average-case and best-case analysis.
Introduces string matching algorithms
Introduces linear programming.

Ability to analyze the performance of algorithms
Ability to choose appropriate data structures and algorithm design methods for a specified application
Ability to understand how the choice of data structures and the algorithm design methods impact the performance of programs

1. Introduction to Algorithms,” T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, Third Edition, PHI.

Fundamentals of Computer Algorithms, Ellis Horowitz, Satraj Sahni and Rajasekharam, Galgotia publications pvt. Ltd.
Design and Analysis Algorithms – Parag Himanshu Dave, Himanshu Bhalchandra Dave Publisher: Pearson
Algorithm Design: Foundations, Analysis and Internet examples, M.T. Goodrich and R. Tomassia, John Wiley and sons.
Data structures and Algorithm Analysis in C++, Allen Weiss, Second edition, Pearson education.