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This unit introduces students to the algorithmic theory and applications of discrete optimisation. The main aims of this unit are: Learn how to model various practical problems as abstract optimisation problems; Learn the theory underlying efficient algorithms for solving these problems; Learn how to use these tools in practice. Specific topics include: Linear and integer programming, polyhedral theory, and approximation algorithms.
Study level | Undergraduate |
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Academic unit | Computer Science |
Credit points | 6 |
Prerequisites:
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(DATA3888 or COMP3888 or COMP3988 or CSEC3888 or SOFT3888 or ENGG3112 or SCPU3001) and (COMP2123 or COMP2823) and (COMP3027 or COMP3927) |
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Corequisites:
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Enrolment in a thesis unit INFO4001 or INFO4911 or INFO4991 or INFO4992 or AMME4111 or BMET4111 or CHNG4811 or CIVL4022 or ELEC4712 or COMP4103 or SOFT4103 or DATA4103 or ISYS4103 |
Prohibitions:
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COMP3530 or COMP5530 |
Assumed knowledge:
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A major in a computer science area. Discrete mathematics and probability (e.g. MATH1064 or equivalent) and Linear algebra (e.g. MATH1061 or equivalent) |
At the completion of this unit, you should be able to:
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Session | MoA ? | Location | Outline ? |
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Semester 2 2024
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Normal day | Camperdown/Darlington, Sydney |
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Session | MoA ? | Location | Outline ? |
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Semester 2 2025
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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