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Unit of study_
BUSS4932: Advanced Optimisation for Business
2024 unit information
This unit covers advanced research-integrated coursework topics in optimisation and stochastic processes, such as convex optimisation, duality, approximation, statistical estimation, random walks and Markov chains, and Poisson and other stochastic processes. The theory is complemented with relevant business examples allowing students to gain a deep understanding of the models and the ability to tailor them to various business applications.
Unit details and rules
Managing faculty or University school:
Business Analytics
| Code | BUSS4932 |
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| Academic unit | Business Analytics |
| Credit points | 6 |
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Prerequisites:
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Students must meet the entry requirements for the Bachelor of Advanced Studies (Advanced Coursework), including completion of a pass undergraduate degree and a major in Business Analytics (including QBUS3600) |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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Students are expected to be familiar with all aspects of Business Analytics, including Optimisation, Regression Modelling, Statistical Modelling and Machine Learning |
At the completion of this unit, you should be able to:
- LO1. Recognise/formulate problems as convex optimization problems
- LO2. Develop code for problems of moderate size
- LO3. Characterize optimal solution, discuss limits of the performance, suggest creative solutions to overcome limits in order to compute the optimal solution
Unit availability
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Modes of attendance (MoA)
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