Topic

Textbook

Weeks 
Introduction: Development of the optimization
methods, types of the problems, setting of Nonlinear Constraint Problem

ch 1. 
0.5 
Onedimensional optimization: Necessary conditions,
Fibonacci and Golden Mean search, Gradient method, Newton Method,
Modifications, Search for global minimum.

3.2.1, 4.1 
1.5 
Review of Linear Algebra and Multivariable Calculus:
Vectors,
Matrices, Projections, Quadratic forms, Gradient, Hessian, Convexity

2.2.12.2.4,
2.2.6, 2.6 
2 
Optimality conditions for Mutivariable problem: Unconstrained
problem, Linear constraints, Nonlinear constraints

3.13.4 
1 
Unconstrained Methods: Nonsmooth functions,
Gradient method, Newton type methods, Non derivative Methods

4.24.6 
2 
Linear constraints: Search directions, Active
set methods, Linear Programming, Quadratic programming

5.1  5.3, 5.6 
3 
Nonlinear constraints: Penally and barrier
methods, Gradient projection methods, Augmented Lagrangian methods, Projected
Lagrangian Method 
6.1  6.5 
2 
Review: Stochastic optimization, Genetic
algorithms, Largescale problems

Notes 
1 
Projects presentation:


1
