• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Academic career UGRD
  • Course convener
    • Dr Paul Scott
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2020
    See Future Offerings

 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:

  1. Be able to apply Linear Programming and Mixed-Integer Programming model to solve real-world problems.
  2. Be able to recognize and formulate convex optimization problems arising in practice.
  3. Demonstrate an understanding of theoretical foundations of convex optimization and be able to use it to characterize optimal solutions to general problems.
  4. Be able to define an appropriate local search neighbourhood for a given problem.
  5. Be able to use a variety of meta-heuristics to escape local minima in a neighbourhood
  6. Demonstrate an understanding of the propagation of a global constraint in a Constraint programming system.

Indicative Assessment

  1. Assignment (50) [LO null]
  2. 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. 

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

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

To enrol in this course you must have completed COMP3620 and have completed MATH1013 or MATH1115. Incompatible with COMP8691.

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
Domestic fee paying students
Year Fee
2020 $4320
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
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

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions