| Module Name | Download |
|---|
| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Lecture 1A : Introduction | Download |
| 2 | Lecture 1B : Isoperimetric problem | Download |
| 3 | Lecture 1C : Review of real analysis (sequences and convergence) | Download |
| 4 | Lecture 2A : Bolzano-Weierstrass theorem and completeness axiom | Download |
| 5 | Lecture 2B : Open sets, closed sets and compact sets | Download |
| 6 | Lecture 2C : Continuity and Weierstrass theorem | Download |
| 7 | Lecture 3A : Weierstrass theorem | Download |
| 8 | Lecture 3B : Different solution concepts | Download |
| 9 | Lecture 3C : Different types of constraints | Download |
| 10 | Lecture 4A : Taylor's theorem | Download |
| 11 | Lecture 4B: First order sufficient condition | Download |
| 12 | Lecture 4C : Second order necessary condition | Download |
| 13 | Lecture 5A : Least square regression | Download |
| 14 | Lecture 5B : Least square regression (continued) | Download |
| 15 | Lecture 5C : Implicit function theorem | Download |
| 16 | Lecture 6A : Optimization with equality constraints and introduction to Lagrange multipliers - I | Download |
| 17 | Lecture 6B :Optimization with equality constraints and introduction to Lagrange multipliers - II | Download |
| 18 | Lecture 6C :Least norm solution of underdetermined linear system | Download |
| 19 | Lecture 7A: Transformation of optimization problems - I | Download |
| 20 | Lecture 7B : Transformation of optimization problems - II | Download |
| 21 | Lecture 7C: Transformation of optimization problems - III | Download |
| 22 | Lecture 8A: Convex Analysis - I | Download |
| 23 | Lecture 8B: Convex Analysis - II | Download |
| 24 | Lecture 8C: Convex Analysis - III | Download |
| 25 | Lecture 9A: Polyhedrons | Download |
| 26 | Lecture 9B: Minkowski-Weyl Theorem | Download |
| 27 | Lecture 9C: Linear Programming Problems | Download |
| 28 | Lecture 10A: Extreme points and optimal solution of an LP | Download |
| 29 | Lecture 10B: Extreme points and optimal solution of an LP (continued) | Download |
| 30 | Lecture 10C: Extreme points and basic feasible solutions | Download |
| 31 | Lecture 11A: Equivalence of extreme point and BFS | Download |
| 32 | Lecture 11B: Equivalence of extreme point and BFS (continued) | Download |
| 33 | Lecture 11C: Examples of Linear Programming | Download |
| 34 | Lecture 12A: Weak and Strong duality | Download |
| 35 | Lecture 12B: Proof of strong duality | Download |
| 36 | Lecture 12C: Proof of strong duality (continued) | Download |
| 37 | Lecture 13A: Farkas' lemma | Download |
| 38 | Lecture 13B: Max-flow Min-cut problem | Download |
| 39 | Lecture 13C: Shortest path problem | Download |
| 40 | Lecture 14A: Complementary Slackness | Download |
| 41 | Lecture 14B: Proof of complementary slackness | Download |
| 42 | Lecture 14C: Tangent cones | Download |
| 43 | Lecture 15A:Tangent cones (continued) | Download |
| 44 | Lecture 15B: Constraint qualifications, Farkas' lemma and KKT | Download |
| 45 | Lecture 16A: KKT conditions | Download |
| 46 | Lecture 16B:Convex optimization and KKT conditions | Download |
| 47 | Lecture 17A: Slater condition and Lagrangian Dual | Download |
| 48 | Lecture 17B: Weak duality in convex optimization and Fenchel dual | Download |
| 49 | Lecture 17C: Geometry of the Lagrangian | Download |
| 50 | Lecture 18A: Strong duality in convex optimization - I | Download |
| 51 | Lecture 18B: Strong duality in convex optimization - II | Download |
| 52 | Lecture 18C: Strong duality in convex optimization - III | Download |
| 53 | Lecture 19A: Line search methods for unconstrained optimization | Download |
| 54 | Lecture 19B: Wolfe conditions | Download |
| 55 | Lecture 19C: Line search algorithm and convergence | Download |
| 56 | Lecture 20A: Steepest descent method and rate of convergence | Download |
| 57 | Lecture 20B: Newton's method | Download |
| 58 | Lecture 20C: Penalty methods | Download |
| 59 | Lecture 21A: L1 and L2 Penalty methods | Download |
| 60 | Lecture 21B: Augmented Lagrangian methods | Download |
| 61 | Lecture 21C: Cutting plane methods | Download |
| 62 | Lecture 22: Interior point methods for linear programming | Download |
| 63 | Lecture 23A: Dynamic programming: Inventory control problem | Download |
| 64 | Lecture 23B: Policy and value function | Download |
| 65 | Lecture 24A: Principle of optimality in dynamic programming | Download |
| 66 | Lecture 24B: Principle of optimality applied to inventory control problem | Download |
| 67 | Lecture 24C: Optimal control for a system with linear state dynamics and quadratic cost | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Lecture 1A : Introduction | PDF unavailable |
| 2 | Lecture 1B : Isoperimetric problem | PDF unavailable |
| 3 | Lecture 1C : Review of real analysis (sequences and convergence) | PDF unavailable |
| 4 | Lecture 2A : Bolzano-Weierstrass theorem and completeness axiom | PDF unavailable |
| 5 | Lecture 2B : Open sets, closed sets and compact sets | PDF unavailable |
| 6 | Lecture 2C : Continuity and Weierstrass theorem | PDF unavailable |
| 7 | Lecture 3A : Weierstrass theorem | PDF unavailable |
| 8 | Lecture 3B : Different solution concepts | PDF unavailable |
| 9 | Lecture 3C : Different types of constraints | PDF unavailable |
| 10 | Lecture 4A : Taylor's theorem | PDF unavailable |
| 11 | Lecture 4B: First order sufficient condition | PDF unavailable |
| 12 | Lecture 4C : Second order necessary condition | PDF unavailable |
| 13 | Lecture 5A : Least square regression | PDF unavailable |
| 14 | Lecture 5B : Least square regression (continued) | PDF unavailable |
| 15 | Lecture 5C : Implicit function theorem | PDF unavailable |
| 16 | Lecture 6A : Optimization with equality constraints and introduction to Lagrange multipliers - I | PDF unavailable |
| 17 | Lecture 6B :Optimization with equality constraints and introduction to Lagrange multipliers - II | PDF unavailable |
| 18 | Lecture 6C :Least norm solution of underdetermined linear system | PDF unavailable |
| 19 | Lecture 7A: Transformation of optimization problems - I | PDF unavailable |
| 20 | Lecture 7B : Transformation of optimization problems - II | PDF unavailable |
| 21 | Lecture 7C: Transformation of optimization problems - III | PDF unavailable |
| 22 | Lecture 8A: Convex Analysis - I | PDF unavailable |
| 23 | Lecture 8B: Convex Analysis - II | PDF unavailable |
| 24 | Lecture 8C: Convex Analysis - III | PDF unavailable |
| 25 | Lecture 9A: Polyhedrons | PDF unavailable |
| 26 | Lecture 9B: Minkowski-Weyl Theorem | PDF unavailable |
| 27 | Lecture 9C: Linear Programming Problems | PDF unavailable |
| 28 | Lecture 10A: Extreme points and optimal solution of an LP | PDF unavailable |
| 29 | Lecture 10B: Extreme points and optimal solution of an LP (continued) | PDF unavailable |
| 30 | Lecture 10C: Extreme points and basic feasible solutions | PDF unavailable |
| 31 | Lecture 11A: Equivalence of extreme point and BFS | PDF unavailable |
| 32 | Lecture 11B: Equivalence of extreme point and BFS (continued) | PDF unavailable |
| 33 | Lecture 11C: Examples of Linear Programming | PDF unavailable |
| 34 | Lecture 12A: Weak and Strong duality | PDF unavailable |
| 35 | Lecture 12B: Proof of strong duality | PDF unavailable |
| 36 | Lecture 12C: Proof of strong duality (continued) | PDF unavailable |
| 37 | Lecture 13A: Farkas' lemma | PDF unavailable |
| 38 | Lecture 13B: Max-flow Min-cut problem | PDF unavailable |
| 39 | Lecture 13C: Shortest path problem | PDF unavailable |
| 40 | Lecture 14A: Complementary Slackness | PDF unavailable |
| 41 | Lecture 14B: Proof of complementary slackness | PDF unavailable |
| 42 | Lecture 14C: Tangent cones | PDF unavailable |
| 43 | Lecture 15A:Tangent cones (continued) | PDF unavailable |
| 44 | Lecture 15B: Constraint qualifications, Farkas' lemma and KKT | PDF unavailable |
| 45 | Lecture 16A: KKT conditions | PDF unavailable |
| 46 | Lecture 16B:Convex optimization and KKT conditions | PDF unavailable |
| 47 | Lecture 17A: Slater condition and Lagrangian Dual | PDF unavailable |
| 48 | Lecture 17B: Weak duality in convex optimization and Fenchel dual | PDF unavailable |
| 49 | Lecture 17C: Geometry of the Lagrangian | PDF unavailable |
| 50 | Lecture 18A: Strong duality in convex optimization - I | PDF unavailable |
| 51 | Lecture 18B: Strong duality in convex optimization - II | PDF unavailable |
| 52 | Lecture 18C: Strong duality in convex optimization - III | PDF unavailable |
| 53 | Lecture 19A: Line search methods for unconstrained optimization | PDF unavailable |
| 54 | Lecture 19B: Wolfe conditions | PDF unavailable |
| 55 | Lecture 19C: Line search algorithm and convergence | PDF unavailable |
| 56 | Lecture 20A: Steepest descent method and rate of convergence | PDF unavailable |
| 57 | Lecture 20B: Newton's method | PDF unavailable |
| 58 | Lecture 20C: Penalty methods | PDF unavailable |
| 59 | Lecture 21A: L1 and L2 Penalty methods | PDF unavailable |
| 60 | Lecture 21B: Augmented Lagrangian methods | PDF unavailable |
| 61 | Lecture 21C: Cutting plane methods | PDF unavailable |
| 62 | Lecture 22: Interior point methods for linear programming | PDF unavailable |
| 63 | Lecture 23A: Dynamic programming: Inventory control problem | PDF unavailable |
| 64 | Lecture 23B: Policy and value function | PDF unavailable |
| 65 | Lecture 24A: Principle of optimality in dynamic programming | PDF unavailable |
| 66 | Lecture 24B: Principle of optimality applied to inventory control problem | PDF unavailable |
| 67 | Lecture 24C: Optimal control for a system with linear state dynamics and quadratic cost | PDF unavailable |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Not Available |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |