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

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

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

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

Prepare: Same graphs for reverse delete algorithm Example

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.

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

Single Source Shortest Path

Prepare Maximum Flow Network Terminology Applications Examples

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