Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
Introduces induced flows, basis matrices, and tree solutions in graph theory.
Introduces the concept of shortest path, discussing weighted paths, Hamiltonian paths, and path optimization algorithms.
Explores network flows, simplex method, linear programming, tree solutions, and dual solutions in optimization problems.
