This module expands on the fundamental concepts of Operations Research and Linear Programming covered in MATH 2804 and MATH 4809. This module introduces a number of non-linear Programming models, including descent methods, conjugate gradient methods, quasi-newton methods, primal methods, and penalty and barrier methods. Case studies of models will be presented
*Curricular information is subject to change
Unconstrained Optimisation:
Optimality conditions.
Descent methods: line search, Newton’s, Golden section search, Fibonacci, secant.
Cauchy’s steepest descent
Conjugate gradient methods
Non-differentiable optimization
Quasi-newton method
Constrained Optimisation:
Optimality conditions
Primal methods
Penalty and barrier methods
Case studies
Lectures and tutorials
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Formal Examination | 100 |