MTH5333 - Discrete optimisation

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Overview

This unit provides an introduction to optimisation over discrete domains using integer programming and combinatorial methods. Discrete optimisation is frequently used to model decision problems in business and industry. This unit covers some of the mathematical tools required to solve these types of problems in practice. Building on linear programming, … For more content click the Read More button below.

This unit provides an introduction to optimisation over discrete domains using integer programming and combinatorial methods. Discrete optimisation is frequently used to model decision problems in business and industry. This unit covers some of the mathematical tools required to solve these types of problems in practice. Building on linear programming, the unit will cover dynamic programming, branch-and-bound, polyhedral analysis, decomposition methods and an introduction to heuristic search for combinatorial optimisation problems.

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Professor Andreas Ernst

Unit Coordinator(s)

Professor Andreas Ernst

Notes

This unit is offered in alternate years commencing Semester 1, 2021

Learning outcomes

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

Develop specialised mathematical knowledge in discrete optimisation.

Understand the profound connections between discrete optimisation, continuous optimisation and combinatorics.

Apply sophisticated combinatorial optimisation and integer programming methods to a variety of practical optimisation problems.

Translate practical problem descriptions into mathematical formulations as discrete optimisation problems and communicate the results to non-technical audiences.

Apply critical thinking in the field of operations research.

Assessment summary

Examination (3 hours and 10 minutes): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: If you would otherwise have passed the unit but who do not achieve at least 45% of the marks available for the end-of-semester examination will receive a Hurdle Fail (NH) grade and a mark of 45 on your transcript.

This unit is offered at both Level 4 and Level 5, differentiated by the level of the assessment. If you are enrolled in MTH5333 you will be expected to demonstrate a higher level of learning in this subject than those enrolled in MTH4333. The assignments and exam in this unit will use some common items from the MTH4333 assessment tasks, in combination with several higher level questions and tasks.

Workload requirements

Workload

Availability in areas of study

Master of Mathematics