Course Information
Course: M.Tech (Computer Science), II Year, 2019
Institution: JIET College, Jodhpur
Prerequisites
Course Description
This course introduces advanced algorithmic techniques for solving complex computational problems. Topics include graph algorithms, matching algorithms, network flows, geometric algorithms, parallel algorithms, randomized algorithms, probabilistic analysis and approximation algorithms.
Course Outcomes
- Analyse advanced graph algorithms and their applications.
- Understand matching and maximum flow techniques.
- Design parallel and randomized algorithms.
- Apply probabilistic methods in algorithm analysis.
- Understand approximation techniques for hard problems.
Course Modules
Module 1: Graph Matching and Network Flow Algorithms
Topics Covered
- Graph matching algorithms
- Network flow problems
- Maximum flow algorithms
Learning Resources
Module 2: Geometrical Algorithms
Topics Covered
- Applications of geometric algorithms
- Divide and conquer techniques
- Convexity and computational geometry
Learning Resources
Module 3: Parallel Algorithms
Topics Covered
- Parallel computation concepts
- PRAM models
- Interconnection networks
- Work-depth model
- Design of parallel algorithms
Learning Resources
Module 4: Randomized and Probabilistic Algorithms
Topics Covered
- Randomized algorithms
- Random variables and expectations
- Probabilistic analysis
Learning Resources
Module 5: Approximation Algorithms and Advanced Data Structures
Topics Covered
- Approximation algorithms
- Self-adjusting data structures
- Persistent data structures
- Multidimensional data structures