AD3351 DESIGN AND ANALYSIS OF ALGORITHMS (DAA)
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Important questions
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UNIT -1
1.Recursive and Non-recursive algorithms**
2.Worst case analysis
UNIT-2
1.Exhaustive Search
2.Divide and conquer method
3.Merge sort – Quick sort – Binary search
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UNIT-3
1.Knapsack Problem**, Prim‟s algorithm
2.Binary Search**
3.Kruskal's Algorithm,Huffman Trees.�
UNIT-4
1.Simplex ,Maximum-Flow Problem**
2.Maximum Matching in Bipartite Graphs
UNIT-5
1.Traveling Salesman problem – Knapsack problem**
2.Backtracking – Hamiltonian Circuit Problem
3.Assignment problem
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PART-C
1.Compulsory Questions {a case study where the student will have to read and analyse the subject }
mostly asked 3,4,5unit (OR) a situation given and you have to write algorithm on your
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*These questions are expected for the exams This may or may not be asked for exams All the best.... from admin Santhosh
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Contact uS
*These questions are expected for the exams This may or may not be asked for exams
All the best.... from admin Santhosh
Thanks for your love and support guys keep supporting and share let the Engineers know about Us and leave a comment below for better improvements
If there is any doubt feel free to ask me I will clear if I can or-else I will say some solutions ..get me through WhatsApp for instant updates _-Stuff SectorSyllabus
UNIT-I INTRODUCTION
Notion of an Algorithm – Fundamentals of AlgorithmicProblem Solving – Important Problem Types – Fundamentals of the Analysis of Algorithmic Efficiency –Asymptotic Notations and their properties. Analysis Framework – Empirical analysis - Mathematical analysis for Recursive and Non-recursive algorithms - Visualization
UNIT-II BRUTE FORCE AND DIVIDE-AND-CONQUER
Brute Force – Computing an – String Matching - Closest-Pair and Convex-Hull Problems - Exhaustive Search - Travelling Salesman Problem - Knapsack Problem - Assignment problem. Divide and Conquer Methodology – Binary Search – Merge sort – Quick sort – Heap Sort - Multiplication of Large Integers – Closest-Pair and Convex - Hull Problems.
UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE
Dynamic programming – Principle of optimality - Coin changing problem, Computing a Binomial Coefficient – Floyd‘s algorithm – Multi stage graph - Optimal Binary Search Trees – Knapsack Problem and Memory functions. Greedy Technique – Container loading problem - Prim‘s algorithm and Kruskal's Algorithm – 0/1 Knapsack problem, Optimal Merge pattern - Huffman Trees.
UNIT IV ITERATIVE IMPROVEMENT
The Simplex Method - The Maximum-Flow Problem – Maximum Matching in Bipartite Graphs, Stable marriage Problem.
UNIT V
COPING WITH THE LIMITATIONS OF ALGORITHM POWER
Limitations of Algorithm Power-Lower-Bound Arguments-Decision Trees-P, NP and NP-
Complete Problems--Coping with the Limitations - Backtracking – n-Queens problem –
Hamiltonian Circuit Problem – Subset Sum Problem-Branch and Bound – Assignment problem –
Knapsack Problem – Travelling Salesman Problem- Approximation Algorithms for NP – Hard
Problems – Travelling Salesman problem – Knapsack problem.
Notion of an Algorithm – Fundamentals of AlgorithmicProblem Solving – Important Problem Types – Fundamentals of the Analysis of Algorithmic Efficiency –Asymptotic Notations and their properties. Analysis Framework – Empirical analysis - Mathematical analysis for Recursive and Non-recursive algorithms - Visualization
UNIT-II BRUTE FORCE AND DIVIDE-AND-CONQUER
Brute Force – Computing an – String Matching - Closest-Pair and Convex-Hull Problems - Exhaustive Search - Travelling Salesman Problem - Knapsack Problem - Assignment problem. Divide and Conquer Methodology – Binary Search – Merge sort – Quick sort – Heap Sort - Multiplication of Large Integers – Closest-Pair and Convex - Hull Problems.
UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE
Dynamic programming – Principle of optimality - Coin changing problem, Computing a Binomial Coefficient – Floyd‘s algorithm – Multi stage graph - Optimal Binary Search Trees – Knapsack Problem and Memory functions. Greedy Technique – Container loading problem - Prim‘s algorithm and Kruskal's Algorithm – 0/1 Knapsack problem, Optimal Merge pattern - Huffman Trees.
UNIT IV ITERATIVE IMPROVEMENT
The Simplex Method - The Maximum-Flow Problem – Maximum Matching in Bipartite Graphs, Stable marriage Problem.
UNIT V
COPING WITH THE LIMITATIONS OF ALGORITHM POWER
Limitations of Algorithm Power-Lower-Bound Arguments-Decision Trees-P, NP and NP-
Complete Problems--Coping with the Limitations - Backtracking – n-Queens problem –
Hamiltonian Circuit Problem – Subset Sum Problem-Branch and Bound – Assignment problem –
Knapsack Problem – Travelling Salesman Problem- Approximation Algorithms for NP – Hard
Problems – Travelling Salesman problem – Knapsack problem.