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Techniques in Operations Research (MAST30013)
Undergraduate level 3Points: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Email: alysson.costa@unimelb.edu.au
Overview
Availability | Semester 1 |
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Fees | Look up fees |
This subject introduces some major techniques and algorithms for solving nonlinear optimisation problems. Unconstrained and constrained systems will be considered, for both convex and non-convex problems. The methods covered include: interval search techniques, Newton and quasi-Newton methods, penalty methods for nonlinear programs, and methods based on duality. The emphasis is both on being able to apply and implement the techniques discussed, and on understanding the underlying mathematical principles. Examples involve the formulation of operations research models for linear regression, multi-facility location analysis and network flow optimisation.
A significant part of the subject is the project, where students work in groups on a practical operations research problem.
Intended learning outcomes
On completion of this subject students should develop
- skills in setting up operations research models;
- a knowledge of the most important techniques for solving nonlinear optimisation problems;
- an understanding of the role of algorithmic thinking in the solution of operations research problems;
- competence in the use of computer packages in operations research;
- an understanding of the factors and restrictions involved in building and using models for planning and management problems.
Generic skills
In addition to learning specific skills that will assist in their future careers in science, students 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;
- computer skills: the ability to use mathematical computing packages.
Last updated: 22 March 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20018 | Discrete Maths and Operations Research | Semester 2 (On Campus - Parkville) |
12.5 |
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: 22 March 2024
Assessment
Additional details
Three written assignments due at regular intervals during semester amounting to a total of up to 50 pages (30%), a group project involving a written report of up to 20 pages due at the end of semester (15%) and a 15-minute oral presentation at the end of semester (5%), and a 2-hour written examination in the examination period (50%).
Last updated: 22 March 2024
Dates & times
- Semester 1
Principal coordinator Alysson Machado Costa Mode of delivery On Campus (Parkville) Contact hours 3 x one hour lectures per week, 1 x one hour practice class per week Total time commitment 170 hours Teaching period 27 February 2017 to 28 May 2017 Last self-enrol date 10 March 2017 Census date 31 March 2017 Last date to withdraw without fail 5 May 2017 Assessment period ends 23 June 2017 Semester 1 contact information
Email: alysson.costa@unimelb.edu.au
Time commitment details
Estimated total time commitment of 170 hours
Last updated: 22 March 2024
Further information
- Texts
Prescribed texts
None
Recommended texts and other resources
H. A. Taha, Operations Research: An Introduction, McMillan, 5th Ed,1992.
W. L. Winston, Operations Research: Applications and Algorithms, PWS-Kent, 1987.
R. Fletcher, Practical Methods of Optimization, 2nd Ed, John Wiley & Sons, NY, 1987.
- Subject notes
This subject is available for science credit to students enrolled in the BSc (both pre-2008 and new degrees), BASc or a combined BSc course.
- Related Handbook entries
This subject contributes to the following:
Type Name Informal specialisation Discrete Mathematics / Operations Research Informal specialisation Science-credited subjects - new generation B-SCI and B-ENG. Informal specialisation Discrete Mathematics / Operations Research Informal specialisation Selective subjects for B-BMED Informal specialisation Operations Research / Discrete Mathematics Major Discrete Mathematics / Operations Research - Breadth options
This subject is available as breadth in the following courses:
- 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.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Last updated: 22 March 2024