| Unit name | Optimisation |
|---|---|
| Unit code | MATH30017 |
| Credit points | 20 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Tadic |
| Open unit status | Not open |
| Pre-requisites |
MATH10003 Analysis 1A and MATH10006 Analysis 1B (or MATH10011 Analysis), MATH11007 Calculus 1 (or MATH10012 ODEs, Curves and Dynamics), and MATH11005 Linear Algebra and Geometry MATH20901 Multivariable Calculus is desirable but not essential |
| Co-requisites |
None |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Unit Aims
The aim of this unit is to make students acquainted with the main concepts, ideas, methods, tools and techniques of the mathematical optimisation.
Unit Description
Optimisation can be described as the processes of selecting a best solution (or a decision) out of available alternatives. As such, optimisation is involved in a number of human activities and almost all branches of natural sciences.
For example, investors seek to create portfolios avoiding excessive risk and achieving high return rates. Manufactures aim to maximize the efficiency of their production processes. Engineers adjust parameters to optimise the performance of their designs. Physical systems tend to a state of a minimum energy. Molecules in an isolated system tend to react with each other until the total potential energy is minimized. Rays of light follow paths minimising their travel time.
Mathematically speaking, optimisation is the process of minimising (or maximizing) a multivariable function subject to constraints on its variables.
At the end of the unit, the students should:
Lectures, problem sheets and office hours.
Formative assessment:
Summative assessment:
Recommended
