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Optimisation for Industry (MAST90014)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | Semester 1 |
|---|---|
| Fees | Look up fees |
The use of mathematical optimisation is widespread in business, where it is a key analytical tool for managing and planning business operations. It is also required in many industrial processes and is useful to government and community organizations. This subject will expose students to operations research techniques as used in industry. A heavy emphasis will be placed on the modelling process that turns an industrial problem into a mathematical formulation. The focus will then be on how to solve the resulting mathematical problem with mixed-integer programming techniques.
Intended learning outcomes
After completing this subject students should be able to:
- Demonstrate a critical understanding of Operations Research techniques and their applications in industry and public decision-making;
- Formulate mathematical optimisation models for industrial decision-making problems;
- Identify appropriate solution methods for mixed-integer programming models;
- Solve optimisation problems arising in industrial frameworks using Python and appropriate black-box solvers.
Generic skills
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:
- Problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
- Analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
- Collaborative skills: the ability to work in a team; and
- Time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 8 November 2024