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Discrete and Network Optimisation (ELEN90087)
Graduate courseworkPoints: 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 2
Email: brazil@unimelb.edu.au
Overview
Availability | Semester 2 |
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Fees | Look up fees |
AIMS
The subject focuses on mathematical concepts and algorithms required for solving and analysing a range of different combinatorial and network optimisation problems.
The subject is intended to prepare students to study fundamental topics in combinatorial optimisation and computational geometry, with an emphasis on finding exact solutions. The course will equip students with tools for modelling discrete and network optimisation problems, solving the optimisation models and analysing the results.
INDICATIVE CONTENT
Topics to be covered include: introduction to spanning trees and matroids; the principles of linear programming; network flow problems and the augmented path algorithm; The Euclidean Steiner tree problem and the GeoSteiner algorithm; integer linear programming; NP-complete problems and Cook’s Theorem.
Intended learning outcomes
Intended Learning Outcomes (ILOs):
On completion of this subject, it is expected that the student should be able to:
- Describe and solve technical problems involving the basic theory underlying the modelling and solving of discrete and network optimisation problems
- Describe the technical challenges in this area and demonstrate the ability to apply the theory to solve a range of relevant problems.
Generic skills
- Ability to apply knowledge of basic science and engineering fundamentals;
- Ability to undertake problem identification, formulation and solution;
- Ability to utilise a systems approach to design and operational performance;
- Expectation of the need to undertake lifelong learning, capacity to do so;
- Capacity for independent critical thought, rational inquiry and self-directed learning;
- Capacity to confront unfamiliar problems;
- Ability to evaluate and synthesise academic research and professional literature;
- Ability to develop models of practical applications and evaluate their performance by rigorous analytical means.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Enrolment in a research higher degree (MPhil or PhD) in Engineering.
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Familiarity with some basic optimisation models and problems is recommended, particularly linear programming, integer programming and minimum spanning tree algorithms.
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: 3 November 2022
Assessment
Additional details
- Continuous assessment, consisting of two written homework assignments not exceeding 30 pages in total and a 15 minute oral presentation requiring 50-60 hours of work. The first assignment will be due mid-semester (approximately week 7). The second assignment and oral presentation will be due in approximately week 11 or 12 (worth 40%);
- A written examination not exceeding three hours at the end of semester (worth 60%).
Hurdle requirement: Students must pass the written exam to pass the subject.
Intended Learning Outcomes (ILOs) 1 and 2 are assessed in the final exam and through the continuous assessment.
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Marcus Brazil Mode of delivery On Campus (Parkville) Contact hours 36 hours of lectures, directed reading, tutorials and project work Total time commitment 200 hours Teaching period 24 July 2017 to 22 October 2017 Last self-enrol date 4 August 2017 Census date 31 August 2017 Last date to withdraw without fail 22 September 2017 Assessment period ends 17 November 2017 Semester 2 contact information
Email: brazil@unimelb.edu.au
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Doctor of Philosophy - Engineering - 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.
Additional information for this subject
Subject coordinator approval required
Last updated: 3 November 2022