IISc Bangalore, , Prof. Shirish K. Shevade
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Updated On 02 Feb, 19
Introduction : Optimization, Types of Problems and Algorithms
Background : Linear Algebra and Analysis,Convex Sets and Convex Functions.
Unconstrained Optimization : Basic properties of solutions and algorithms, Global convergence.
Basic Descent Methods : Line Search Methods, Steepest Descent and Newton Methods,Modified Newton methods, Globally convergent Newton Method,Nonlinear Least Squares Problem and Algorithms,Conjugate Direction Methods,Trust-Region Methods.
Constrained Optimization : First Order Necessary Conditions, Second Order Necessary Conditions, Duality, Constraint Qualification,Convex Programming Problem and Duality.
Linear Programming : The Simplex Method, Duality and Interior Point Methods, Karmarkar's algorithm,Transportation and Network flow problem.
Quadratic Programming : Active set methods, Gradient Projection methods and sequential quadratic programming.
Dual Methods : Augmented Lagrangians and cutting-plane methods,Penalty and Barrier Methods,Interior Point Methods.
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Numerical Optimization by Dr. Shirish K. Shevade, Department of Computer Science and Engineering, IISc Bangalore. For more details on NPTEL visit httpnptel.iitm.ac.in
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
March 29, 2019
Great course. Thank you very much.