• Offered by School of Computing
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Academic career UGRD
  • Course convener
    • Jose Iria
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2022
    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.

Other Information

Professional Skills Mapping:

Mapping of Learning Outcomes to Assessment and Professional Competencies

Indicative Assessment

  1. Assignment (50) [LO null]
  2. Final Exam (hurdle) (50) [LO null]

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.  

Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found 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
2022 $4740
International fee paying students
Year Fee
2022 $6000
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
7402 25 Jul 2022 01 Aug 2022 31 Aug 2022 28 Oct 2022 In Person N/A

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