This course provides foundations and plenty of exercises in practical optimisation problems, while covering all basic elements of optimisation including forms of constraint programming as well as variations on linear programming and convex optimisation.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Be able to apply Linear Programming and Mixed-Integer Programming model to solve real-world problems.
- Be able to recognize and formulate convex optimization problems arising in practice.
- Demonstrate an understanding of theoretical foundations of convex optimization and be able to use it to characterize optimal solutions to general problems.
- Be able to define an appropriate local search neighbourhood for a given problem.
- Be able to use a variety of meta-heuristics to escape local minima in a neighbourhood
- Demonstrate an understanding of the propagation of a global constraint in a Constraint programming system.
Indicative Assessment
- Assignment (50) [LO null]
- Final Exam (hurdle) (50) [LO null]
In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle.
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Workload
Up to 60 hours of total face-time, which includes interactions with lectures and tutors. Up to 60 hours of total preparation, repeat, assignment and practical exercise time.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
None
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2020 | $4320 |
- International fee paying students
| Year | Fee |
|---|---|
| 2020 | $5760 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 9531 | 27 Jul 2020 | 03 Aug 2020 | 31 Aug 2020 | 30 Oct 2020 | In Person | N/A |
