Course Title: Advanced Optimisation

Part A: Course Overview

Course Title: Advanced Optimisation

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1326

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 2 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2015

MATH1326

City Campus

Postgraduate

171H School of Science

Face-to-Face

 Sem 2 2020,
Sem 1 2022

Course Coordinator: Assoc. Prof. Melih Ozlen

Course Coordinator Phone: +61 3 9925 3007

Course Coordinator Email: melih.ozlen@rmit.edu.au

Course Coordinator Location: 15.4.11

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Required Prior Study

You should have satisfactorily completed following course/s before you commence this course.

Alternatively, you may be able to demonstrate the required skills and knowledge before you start this course.

Contact your course coordinator if you think you may be eligible for recognition of prior learning.

Assumed Knowledge

Elementary knowledge of Programming (or commitment to learn at the start of the semester)


Course Description

Optimisation models are amongst the most widely used models in analytics and data science. They are used to solve a diverse range of problems comprising telecommunications, transport, timetabling, scheduling, workforce planning, loading, cutting and more. This course concentrates on formulating and building such real-life models, solving them using a programming language and commercial optimisation software and interpreting their solution.  The course will also introduce more advanced methods useful for solving large scale optimisation problems.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for MC004 Master of Statistics and Operations Research, MC242 Master of Analytics and MC267 Master of Data Science:

Personal and professional awareness

  • the ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
  • the ability to reflect on experience and improve your own future practice
  • the ability to apply the principles of lifelong learning to any new challenge.

Knowledge and technical competence

  • an understanding of appropriate and relevant, fundamental and applied mathematical knowledge, methodologies and modern computational tools.

Problem-solving

  • the ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
  • an understanding of the relationship between the purpose of a model and the appropriate level of complexity and accuracy.

Communication

  • the ability to effectively communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral), and to tailor the style and means of communication to different audiences.  Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.

Information literacy

  • the ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.


On completion of this course, you should be able to:

  1. Understand the power of mathematical programming and utilise its wide range of applications;
  2. Formulate and solve advanced real life mixed integer programming (MIP) problems using a programming language;
  3. Implement MIP models using a programming language and commercial software;
  4. Apply heuristic optimisation techniques to solve challenging problems;
  5. Interpret and verify solutions to MIP problems. 


Overview of Learning Activities

 

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.


Overview of Learning Resources

 

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks

Assessment Task 1:  Practical Assessment 1
Weighting 25%
This assessment task supports CLOs 1, 2, 3 and 5

Assessment Task 2: Practical Assessment 2
Weighting 35%
This assessment task supports CLOs 1, 2, 3, 4 and 5

Assessment Task 3: Practical Assessment 3
Weighting 40%
This assessment task supports CLOs 1, 2, 3, 4 and 5

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.