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Course Contents: T1

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.

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Course Contents: T1

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  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-IGreedy Algorithms: ContentsIntroduction to Greedy algorithm and basic principleExamples:Knapsack problem: Principle, numerical example, algorithm, complexity calculation, Minimum Cost Spanning Tree:Prims Algorithm, Reverse Delete AlgorithmSingle source shortest path algorithm: DijkastraAlgorithm, 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

  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

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