Book Details

Design and Analysis of Algorithms (Brute Force, Iterative Improvement)

Design and Analysis of Algorithms (Brute Force, Iterative Improvement)

Published by uLektz

Course Code : ULZ0059
Author : uLektz
University : General for All University
Regulation : 2017
Categories : Computer Science
Format : ico_bookePUB3 (DRM Protected)
Type :

eBook

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Description :Design and Analysis of Algorithms (Brute Force, Iterative Improvement) of ULZ0059 covers the latest syllabus prescribed by General for All University for regulation 2017. Author: uLektz, Published by uLektz Learning Solutions Private Limited.

Note : No printed book. Only ebook. Access eBook using uLektz apps for Android, iOS and Windows Desktop PC.

Topics
UNIT I INTRODUCTION

1.1 Notion of an Algorithm

1.2 Fundamentals of Algorithmic Problem Solving

1.3 Important Problem Types

1.4 Fundamentals of the Analysis of Algorithm Efficiency - Analysis Framework

1.5 Asymptotic Notations and its properties

1.6 Mathematical analysis for Recursive and Non-recursive algorithms.

UNIT II BRUTE FORCE AND DIVIDE-AND-CONQUER

2.1 Brute Force - Closest-Pair and Convex-Hull Problem - Exhaustive Search, Traveling Salesman Problem, Knapsack Problem, Assignment problem.

2.2 Divide and conquer methodology - Merge sort - Quick sort - Binary search

2.3 Multiplication of Large Integers - Strassen’s Matrix Multiplication

2.4 Closest-Pair and Convex-Hull Problems.

UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE

3.1 Computing a Binomial Coefficient

3.2 Warshall’s and Floyd’ algorithm

3.3 Optimal Binary Search Trees

3.4 Knapsack Problem and Memory functions.

3.5 Greedy Technique

3.6 Prim’s algorithm

3.7 Kruskal's Algorithm

3.8 Dijkstra's Algorithm

3.9 Huffman Trees.

UNIT IV ITERATIVE IMPROVEMENT

4.1 The Simplex Method

4.2 The Maximum-Flow Problem

4.3 Maximum Matching in Bipartite Graphs

4.4 The Stable marriage Problem.

UNIT V COPING WITH THE LIMITATIONS OF ALGORITHM POWER

5.1 Limitations of Algorithm Power - Lower-Bound Arguments

5.2 Decision Trees - P and NP - NP-Complete Problems

5.3 Coping with the Limitations

5.4 Backtracking - n-Queens problem - Hamiltonian Circuit Problem - Subset Sum Problem

5.5 Branch and Bound-Assignment problem - Knapsack Problem - Traveling Salesman Problem

5.6 Approximation Algorithms for NP - Hard Problems - Traveling Salesman problem - Knapsack problem.

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