Linear Programming Course Video

  • Lecture 1 - Production planning [video]
  • Lecture 2 - Introduction to mathematical programming[video]
  • Lecture 3 - Piecewise linear functions [video]
  • Lecture 4 - Fourier-Motzkin Procedure [video]
  • Lecture 5 - Convex hull [video]
  • Lecture 6 - Extreme point, vertex, basic feasible solution [video]
  • Lecture 7 - Equivalence of extreme point, vertex, basic feasible solution [video]
  • Lecture 8 - Existence of extreme points [video]
  • Lecture 9 - What do optimal solutions look like[video]
  • Lecture 10 - Why bother about extreme points [video]
  • Lecture 11 - Standard form polyhedron [video]
  • Lecture 12 - BFS of standard form [video]
  • Lecture 13 - Introduction to degeneracy [video]
  • Lecture 14 - Local optimal solution equals global optimal solution for convex optimization [video]
  • Lecture 15 - Proving optimality of BFS [video]
  • Lecture 16 - Development of the simplex algorithm [video]
  • Lecture 17 - Simplex algorithm and degeneracy [video]
  • Lecture 18 - Bland's rule [video]
  • Lecture 19 - Phase 1 simplex algorithm [video]
  • Lecture 20 - Importance of dual bounds [video]
  • Lecture 21 - Constructing the dual LP [video]
  • Lecture 22 - Weak and strong duality [video]
  • Lecture 23 - Two consequences of strong duality [video]
  • Lecture 24 - Affine form of Farkas lemma [video]
  • Lecture 25 - From Farkas lemma to strong duality [video]
  • Lecture 26 - Separation theorem [video]
  • Lecture 27 - From separation theorem to Farkas Lemma [video]
  • Lecture 28 - Recession cone [video]
  • Lecture 29 - Unbounded LPs and recession cone[video]
  • Lecture 30 - Representation theorem [video]
  • Lecture 31 - Calculating dimension of a set [video]
  • Lecture 32 - LP Sensitivity [video]
  • Lecture 33 - Value function of an LP [video]
  • Lecture 34 - Dantzig-Wolfe decomposition [video]
  • Lecture 35 - Dantzig-Wolfe decomposition contd. [video]
  • Lecture 36 - Bender's decomposition [video]
  • Lecture 37 - Solving LP equals to solving linear inequalities [video]
  • Lecture 38 - Preliminaries of the ellipsoid algorithm [video]
  • Lecture 39 - The ellipsoid [video]
  • Lecture 40 - Ellipsoid method - reduction in volume in each iteration [video]
  • Lecture 41 - Preprocessing for the ellipsoid algorithm [video]
  • Lecture 42 - Volume of the full-dimensional polytope [video]
  • Lecture 43 - Wrapping up the ellipsoid algorithm [video]
  • Lecture 44 - Polarity [video]
  • Lecture 45 - Separation = optimization [video]