6 points, SCA Band 2, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Not offered in 2019
Enrolment in the Master of Mathematics and
This unit is offered in alternate years commencing Semester 1, 2020
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.
On completion of this unit students will 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.
Examination (3 hours): 60% (Hurdle)
Continuous assessment: 40%
Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.
- 3 hours of lectures
- 1-hour tutorial and
- 8 hours of independent study per week
See also Unit timetable information
This unit applies to the following area(s) of study
Master of Mathematics