Overview

This unit introduces some of the fundamental methods from operations research and computational mathematics for continuous optimisation problems. A range of such optimisation problems appear in economics, engineering, finance, business, data science and many other application areas. You will receive an introduction to the mathematical theory of continuous optimisation with … For more content click the Read More button below.

Offerings

S1-01-CLAYTON-ON-CAMPUS

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Dr Janosch Rieger

Unit Coordinator(s)

Dr Janosch Rieger

Notes

You are required to bring your own device, such as a laptop, on which you can complete computational exercises, to the applied classes

Learning outcomes

On successful completion of this unit, you should be able to:
1.

Formulate a range of operations research problems as linear programming problems, and be able to solve them computationally;

2.

Demonstrate an understanding how the most widely used linear programming algorithms work;

3.

Apply duality theory to prove optimality of a solution;

4.

Interpret the solutions of optimisation problems, including analysing sensitivity of solutions;

5.

Implement several iterative algorithms for solving unconstrained non-linear optimisation problems and understand the mathematics behind these;

6.

Formulate and solve general non-linear programs arising in engineering, data science and other areas.

Assessment

1 - Continuous assessment
2 - Examination (3 hours and 10 minutes)

Scheduled and non-scheduled teaching activities

Applied sessions
Lectures

Workload requirements

Workload

Learning resources

Required resources
Technology resources

Other unit costs

Costs are indicative and subject to change.
Miscellaneous items required (Unit course reader, Printing, Stationery) - $120.

Availability in areas of study

Applied mathematics
Financial and insurance mathematics
Mathematical statistics
Mathematics
Pure mathematics