Course Contents
Unconstrained Optimization: Basics of set-constrained and unconstrained optimization: Conditions for local minimizers. One-dimensional search methods: Golden Section search, Newton’s method, Secant method, Line search method. Gradient methods: The method of steepest descent, Analysis of gradient methods. Newton’s Method: Analysis of Newton’s method, Levenberg-Marquardt modification, Non-linear least squares. Conjugate Direction Methods: Conjugate direction and conjugate gradient algorithm, Conjugate gradient algorithm for non-quadratic problems. Quasi-Newton Methods: Approximating the inverse Hessian, The rank one correction formula. Least-squares Analysis, Recursive Least Square algorithm, Solution of by minimizing , Kacmarz’s algorithm, Solving in general, Genetic Algorithms.
Linear Programming Problems: Introduction to linear programming, Simplex method, Duality, Non-Simples methods.
Nonlinear Constrained Optimization: Problems with equality constraints: Introduction, Problem Formulation, Tangent and Normal Spaces, Lagrange condition, Second-order conditions, Minimizing quadratics subject to linear constraints. Problems with inequality constraints: Karush-Kuhn-Tucker condition, Second-Order conditions. Convex optimization problems.
Linear Programming Problems using Duality Theory
View Now
Constrained and Unconstrained Optimization Problems
View Now
Convex Optimization
View Now
Book Title : An Introduction to Optimization
Author : Edwin K. P. Chong & Stanislaw H. Zak
Edition : 2nd Edition
Publisher : JOHN WILEY & SONS, INC
Title : Course Outline
Type : Other
View Course Outline
Title : Weekly Plan
Type : Other
View Weekly Plan
Title : An Introduction to Optimization by Edwin K.P. Chong & Stanislaw H. Zak
Type : Reference Book
View An Introduction to Optimization by Edwin K.P. Chong & Stanislaw H. Zak
Title : Chapter 17: Duality
Type : Presentation
View Chapter 17: Duality
Title : Chapter 12: Least Square Analysis
Type : Presentation
View Chapter 12: Least Square Analysis
Title : Problems with Equality Constraints
Type : Presentation
View Problems with Equality Constraints
Title : Problems with Inequality Constraints
Type : Presentation
View Problems with Inequality Constraints
Title : Chapter 21: Convex Optimization
Type : Presentation
View Chapter 21: Convex Optimization