MTH301/HMTH221 Optimization

Lecturer: Dr M B Petrov

Duration :1 semester

Prerequisites :NONE

Courses for which this is pre- or co- requisite :HMTH333

Core Course for Major, minor

Aim:

To introduce students to significant methods for linear and non-linear optimization. The algorithms are developed neuristically with rigorous justification where suitable. Descriptions of the methods are accompanied by the algorithms in a form suitable for computer implementation.

Course Outline:

Optimization of one-dimensional functions: conditions for a local minimum, golden-section search, Powell's method, Newton-Raphson method.	8
Multidimensional unconstrained optimization: direct methods (simples, Hooke and Jeeves', conjugate directions), gradient methods (steepest descent, modified Newton-Raphson, linear programming.	8
Nonlinear constrained optimization: method of Lagrange, Kuhn-Tucker conditions, penalty-function techniques.	8

Recommended Texts:

• B S Gottried & J Weisman, Introduction to optimization theory. (Prentice Hall, 1973)
• R Fletcher, Practical methods of optimization (Wiley 1980).