1. Course Contents: T1 Greedy Algorithm Divide & Conquer
Dynamic Programming
Three questions 10 marks each [30 marks]
Time 1.5 hrs [Paper on Sunday]
No extra answer sheet
Presentation of solution will be counted

2. Unit-3:Part-1
UNIT-III:  Part-I Greedy Algorithms: Contents Introduction to Greedy algorithm and basic principle Examples: Knapsack problem: Principle, numerical example, algorithm, complexity calculation, Minimum Cost Spanning Tree: Prims Algorithm, Reverse Delete Algorithm Single source shortest path algorithm: Dijkastra Algorithm, Job Sequencing Problem: [Assignment on case study] Maximum Flow Problem: Theory, numerical, example and application, Methodology to compute complexity of algorithm with each topic

3. Prepare Knapsack Algorithm Basic Idea Numerical
Algorithm and time complexity [Capacity rule]
Various applications of Knapsack Algorithm
Example: n=7 Capacity:12: All three methods/Best method
Object 1 2 3 4 5 6 7
Profit 12 9 16 10
Weight

4. Prepare Prims Algorithm Graph – Cost matrix
Start with minimum [Function to find minimum]
Role of intermediate data structures [near array]
Representation of output [Three tuple form]
Examples
Algorithm
Heap structure and its advantage

5. Prepare: Same graphs for reverse delete algorithm
Example

6. Reverse Delete Algorithm
Data structure used in implementation
Additional storage required
How to find alternate path to reach a vertex
Suggested questions:?
Check graph and solve.

7. Prepare Single Source Shortest path Distance formula, parent array,
Vertex selected array
Steps: intermediate process.
Distance tree
What will happen if cycle and
negative edges are permitted

8. Single Source Shortest Path

9. Prepare
Maximum Flow Network
Terminology
Applications
Examples

10. Job Sequencing problem
Principle
Applications
Example: Snippet/Snapshot
Mathematical formulation
Scheduling with deadline/without deadline