Numerical Optimization

Numerical Optimization
Numerical Optimization by Dr. Shirish K. Shevade, Department of Computer Science and Engineering, IISc Bangalore. For more details on NPTEL visit
Mod-01 Lec-01 Introduction
Mod-02 Lec-02 Mathematical Background
Mod-02 Lec-03 Mathematical Background (contd)
Mod-03 Lec-04 One Dimensional Optimization - Optimality Conditions
Mod-03 Lec-05 One Dimensional Optimization (contd)
Mod-04 Lec-06 Convex Sets
Mod-04 Lec-07 Convex Sets (contd)
Mod-05 Lec-08 Convex Functions
Mod-05 Lec-09 Convex Functions (contd)
Mod-06 Lec-10 Multi Dimensional Optimization - Optimality Conditions, Conceptual Algorithm
Mod-06 Lec-11 Line Search Techniques
Mod-06 Lec-12 Global Convergence Theorem
Mod-06 Lec-13 Steepest Descent Method
Mod-06 Lec-14 Classical Newton Method
Mod-06 Lec-15 Trust Region and Quasi-Newton Methods
Mod-06 Lec-16 Quasi-Newton Methods - Rank One Correction, DFP Method
Mod-06 Lec-17 Quasi-Newton Methods - Rank One Correction, DFP Method
Mod-06 Lec-18 Conjugate Directions
Mod-06 Lec-19 Quasi-Newton Methods - Rank One Correction, DFP Method
Mod-07 Lec-20 Constrained Optimization - Local and Global Solutions, Conceptual Algorithm
Mod-07 Lec-21 Feasible and Descent Directions
Mod-07 Lec-22 First Order KKT Conditions
Mod-07 Lec-23 Constraint Qualifications
Mod-07 Lec-24 Convex Programming Problem
Mod-07 Lec-25 Second Order KKT Conditions
Mod-07 Lec-26 Second Order KKT Conditions (contd)
Mod-08 Lec-27 Weak and Strong Duality
Mod-08 Lec-28 Geometric Interpretation
Mod-08 Lec-29 Lagrangian Saddle Point and Wolfe Dual
Mod-09 Lec-30 Linear Programming Problem
Mod-09 Lec-31 Geometric Solution
Mod-09 Lec-32 Basic Feasible Solution
Mod-09 Lec-33 Optimality Conditions and Simplex Tableau
Mod-09 Lec-34 Simplex Algorithm and Two-Phase Method
Mod-09 Lec-35 Duality in Linear Programming
Mod-09 Lec-36 Interior Point Methods - Affine Scaling Method
Mod-09 Lec-37 Karmarkar's Method
Mod-10 Lec-38 Lagrange Methods, Active Set Method
Mod-10 Lec-39 Active Set Method (contd)
Mod-10 Lec-40 Barrier and Penalty Methods, Augmented Lagrangian Method and Cutting Plane Method