MATH412-12S2 (C)
Unconstrained Optimization
This is a semester two course.
Course Information
This course looks at the minimization of smooth functions of several variables. The first part of the course examines gradient based methods using line searches, including Newton, quasi-Newton, and conjugate gradient methods.
A selection of other topics is then introduced, including trust region methods and methods for constrained optimization.
Demonstration software is used to illustrate aspects of various algorithms in practice.
Enquiries
Dr Chris Price
Room 601 Erskine Building
Phone Extension 7682