Techniques in Operations Research (MAST30013)

Undergraduate level 3Points: 12.5On Campus (Parkville)

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Overview

Availability
Semester 1
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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: 20 March 2025

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: 20 March 2025

Assessment

DescriptionTimingPercentage

Two written assignments (due in weeks 4 or 5 and 10 or 11 respectively)

  • 500 words
From Week 4 to Week 1012%

Mid-semester in-class assessment (20 minutes)

  • 20 minutes
Week 78%

A group project involving a written report of up to 5 pages per student

  • 5 pages
End of semester15%

An oral presentation on the group project of about 4 minutes per person

  • 4 minutes
End of semester5%

A written examination

  • 2 hours
During the examination period60%

Last updated: 20 March 2025

Dates & times

  • Semester 1
    CoordinatorJoyce Zhang
    Mode of deliveryOn Campus (Parkville)
    Contact hours3 x one hour lectures per week, 1 x one hour practice class per week
    Total time commitment170 hours
    Teaching period26 February 2024 to 26 May 2024
    Last self-enrol date 8 March 2024
    Census date 3 April 2024
    Last date to withdraw without fail 3 May 2024
    Assessment period ends21 June 2024

    Semester 1 contact information

    lele.zhang@unimelb.edu.au

Time commitment details

Estimated total time commitment of 170 hours

What do these dates mean

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  • 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: 20 March 2025

Further information

Last updated: 20 March 2025