Pramesh Kumar

Course syllabus

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Lectures

• Lecture 1: Introduction to the course
• Lecture 2: Elementary definitions in Graph Theory
• Lecture 3: Analysis of algorithms and computational complexity
• Lecture 4: Elementary data structures
• Lecture 5: Modeling optimization problems
• Lecture 6: Simplex method
• Lecture 7: Linear programming duality
• Lecture 8: Dynamic Programming
• Lecture 9: Graph search
• Lecture 10: Shortest path
• Lecture 11: Minimum spanning tree
• Lecture 12: Max flow min cut
• Lecture 13: Min cost flow
• Lecture 14: Matching in bipartite graphs
• Lecture 15: Introduction to integer programming

Jupyter notebooks

• Introduction to networkx
• Sorting algorithms
• Read a model from a file and solve it using gurobipy
• model.lp file
• Solving network flow problems with networkx and gurobipy
• Graph search algorithms

Miscellaneous

• Instructions on installing Python and gurobipy

Assignments and Project

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