Introduction to Optimization
MATP6600 / ISYE6780
Handwritten notes from Nonlinear Programming:
Optimality conditions for nonlinear programming
Subspaces, affine sets,
convex sets, and cones
2 theorems on convex functions
smooth convex functions (Lecture 5).
Extreme points and rays,
Dimension and faces
An iteration of the
An example of
solving a Lagrangian dual problem.
packages on NEOS.
For a more detailed survey of nonlinear programming algorithms,
by Leyffer and Mahajan.
by Boyd and Vandenberghe.
nonlinear programming FAQ, including links to collections of
The NEOS Server
has some nonlinear programming packages available.
introduction to the conjugate gradient method without the agonizing pain,
by Jonathan Shewchuk.
A survey of pattern
search and related methods
of the Mathematical Optimization Society newsletter
discussing smoothing methods.
Slides on the
alternating direction method of multipliers,
by Stephen Boyd.
Here's the underlying
John Mitchell's homepage
Dept of Mathematical Sciences Course Materials