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Network Optimisation (MAST90013)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Overview
Availability | Semester 2 - Dual-Delivery |
---|---|
Fees | Look up fees |
Many practical problems in management, operations research, telecommunication and computer networking can be modelled as optimisation problems on networks. Here the underlying structure is a graph. This subject is an introduction to optimisation problems on networks with a focus on theoretical results and efficient algorithms. It covers classical problems that can be solved in polynomial time, such as shortest paths, maximum matchings, maximum flows, and minimum cost flows. Other topics include complexity and NP-completeness, matroids and greedy algorithms, approximation algorithms, multicommodity flows, and network design. This course is beneficial for all students of discrete mathematics, operations research, and computer science.
Intended learning outcomes
After completing this subject, students should:
- be able to understand aspects of network optimisation problems and the methodologies to solve them;
- develop the abilities needed to design combinatorial algorithms for solving other network problems not covered in the subject;
- have the ability to pursue further studies in this 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: 31 January 2024
Eligibility and requirements
Prerequisites
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST30011 | Graph Theory | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
Or equivalent
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
An introductory-level subject in operations research equivalent to
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST20018 | Discrete Maths and Operations Research | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
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: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Up to 50 pages of written assignments (two assignments worth 15% each, due mid and late in semester)
| Second half of the teaching period | 30% |
A written examination
| During the examination period | 70% |
Additional details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Dates & times
- Semester 2
Coordinator Sanming Zhou Mode of delivery Dual-Delivery (Parkville) Contact hours 36 hours comprising 1x 2-hour lecture per week and 1x 1-hour practice class per week. Total time commitment 170 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022
Time commitment details
170 hours
Additional delivery details
This Dual-Delivery subject has On Campus assessment components.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Lecture notes prepared by Dr Sanming Zhou, and the textbook by B. Korte and J. Vygen, Combinatorial Optimiation: Theory and Algorithms. 2nd Edition, Springer, Berlin, 2002
Recommended texts and other resources
TBA
- 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.
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
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024