Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject is not offered in 2015.
|Time Commitment:||Contact Hours: 36 hours of lectures |
Total Time Commitment:
Enrolment in a research higher degree (Masters or PhD) in Engineering
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|Non Allowed Subjects:|| |
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/
Dr. Marcus Brazil
This subject provides a rigorous introduction to the mathematics of optimization, as used across all of science and particularly in engineering design. There is an emphasis on both the theory and application of optimization techniques, with a focus on fundamental areas such as convex optimization and/or discrete optimization. This subject is intended for research higher-degree students in engineering.
Topics may include:
INTENDED LEARNING OUTCOMES (ILO)
Having completed this subject it is expected that the student be able to:
Hurdle requirement: Students must pass the written exam to pass the subject.
ILOs 1 to 3 are assessed in the final exam and the submitted assignments.
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This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
LEARNING AND TEACHING METHODS
The subject is delivered through lectures and homework assignments
INDICATIVE KEY LEARNING RESOURCES
Students are provided with lecture notes, including worked examples, assignment problems, and recommended reading lists comprising textbooks and journal articles.
CAREERS / INDUSTRY LINKS
Exposure to research literature and the rigour expected at the level of postgraduate study.
Master of Philosophy - Engineering |
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