Scheduling and Optimisation (MAST90050)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | Semester 2 |
|---|---|
| Fees | Look up fees |
Scheduling is critical to manufacturing, mining, and logistics, and is of increasing importance in healthcare and service industries. Most automated systems, ranging from elevators to industrial robots, embed some kind of scheduling algorithms. Building on the Optimisation background provided in Optimisation for Industry, this subject teaches students how to solve more advanced problems. A particular focus will be scheduling problems, but other more general assignment problems will be discussed.
Intended learning outcomes
After completing this subject, students should be able to:
- Apply advanced mathematical and computing techniques to model scheduling problems;
- Develop effective mathematical methods of scheduling;
- Apply such methods in important real-life situations;
- Utilise key foundational knowledge to pursue further studies in this discipline and related areas.
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;
- time-management skills: the ability to meet regular deadlines while balancing competing commitments.
Last updated: 4 March 2025
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST90014 | Optimisation for Industry | Semester 1 (On Campus - Parkville) |
12.5 |
Or equivalent
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 4 March 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
A written assignment of up to 20 pages ( approx. 25 hours time committment)
| Mid semester | 25% |
One group project including a report of up to 20 pages to be submitted in weeks 3 or 4, and a 10 minute group presentation or one page proposal due during weeks 9 - 12.
| Throughout the semester | 25% |
A written examination
| During the examination period | 50% |
Last updated: 4 March 2025
Dates & times
- Semester 2
Coordinator Joyce Zhang Mode of delivery On Campus (Parkville) Contact hours One 2-hour lecture per week and one 1-hour computer lab/practical class per week. Total time commitment 170 hours Teaching period 28 July 2025 to 26 October 2025 Last self-enrol date 8 August 2025 Census date 1 September 2025 Last date to withdraw without fail 26 September 2025 Assessment period ends 21 November 2025 Semester 2 contact information
Time commitment details
170 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 4 March 2025
Further information
- Texts
- Related Handbook entries
This subject contributes to the following:
Type Name Course Ph.D.- Engineering Course Master of Science (Mathematics and Statistics) Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering Informal specialisation Mathematics and Statistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
Last updated: 4 March 2025