Master of Operations Research and Analytics specialisation in Operations Research and Analytics - Taught 180

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Sometimes referred to as “the science of better”, Operations Research is a method of solving decision-making problems that involve the use of scarce or valuable resources. Its core focus is the optimisation of resources and process flows, applicable to real-world challenges such as profit maximisation, performance or yield, minimising costs, and risk management, making it an increasingly valuable field to most organisations today.

Our Department of Engineering Science boasts several experts in data-driven decision-making who actively pursue collaborative relationships with research, public and private industries worldwide. As part of the Operations Research and Computational Analytics (ORCA) group, they experiment with theory, algorithms and computational methods to develop efficient systems that are currently used in our everyday lives.

Operations Research is covered at an undergraduate level in our Bachelor of Engineering (Honours) in Engineering Science, with options to explore this specialisation’s many applications in our postgraduate programmes. Its approach is often interdisciplinary – employing techniques that include data analysis, statistics, mathematical modelling, optimisation and computing – and can therefore be potentially pursued by students with backgrounds in engineering, science, commerce and arts.

You will familiarise yourself with theory and methodology in your postgraduate programme. Topics such as optimisation under uncertainty, and network design and simulation are common.
The broad, interdisciplinary nature of operations research makes it a field with extensive variety – it is utilised in many industries, with many opportunities arising continuously for new applications. As a postgraduate student, your main challenge may involve finding new areas or aspects for you to contribute to.

Some of the projects we have undertaken include:
- Delivery and policy analysis for the healthcare industry
- Optimising transportation systems, including airlines and yachts
- Route simulation and optimisation for emergency vehicles
- Electricity and telecommunications network design

Our graduates tend to apply their research and methodological competencies to a variety of industries, including health, transport, telecommunications, broadcasting, mining and utilities. They often pursue positions as analysts or consultants, contributing to improvements in the design, performance and management of large, complex systems.

Complete 180 points comprising:

60 points from Group 1 Elective Courses, and
45 points from Group 2 Elective Courses, and
30 points from Group 3 Elective Courses, and
Either:
45 points for all Research Project - 1 Semester, or
45 points for all Research Project - 2 Semesters

Group 1 Elective Courses

Complete exactly 60 points from the following:

ENGSCI 760 - Algorithms for Optimisation (15 points)

ENGSCI 761 - Integer and Multi-objective Optimisation (15 points)

ENGSCI 763 - Advanced Simulation and Stochastic Optimisation (15 points)

ENGSCI 765 - Advanced Optimisation in Operations Research (15 points)

ENGSCI 768 - Advanced Operations Research and Analytics (15 points)

STATS 720 - Stochastic Processes (15 points)

STATS 723 - Stochastic Methods: Theory and Applications (15 points)

STATS 783 - Simulation and Monte Carlo Methods (15 points)

Group 2 Elective Courses

Complete exactly 45 points from the following:

COMPSCI 753 - Algorithms for Massive Data (15 points)

COMPSCI 760 - Advanced Topics in Machine Learning (15 points)

COMPSCI 761 - Advanced Topics in Artificial Intelligence (15 points)

COMPSCI 762 - Foundations of Machine Learning (15 points)

ENGSCI 712 - Computational Algorithms for Signal Processing (15 points)

ENGSCI 755 - Decision Making in Engineering (15 points)

OPSMGT 766 - Fundamentals of Supply Chain Coordination (15 points)

SOFTENG 753 - Machine Learning Techniques and Applications (15 points)

STATS 726 - Time Series (15 points)

STATS 731 - Bayesian Inference (15 points)

STATS 763 - Advanced Regression Methodology (15 points)

STATS 769 - Advanced Data Science Practice (15 points)

Group 3 Elective Courses

Complete exactly 30 points from the following:

ENGSCI 760 - Algorithms for Optimisation (15 points)

ENGSCI 761 - Integer and Multi-objective Optimisation (15 points)

ENGSCI 763 - Advanced Simulation and Stochastic Optimisation (15 points)

ENGSCI 765 - Advanced Optimisation in Operations Research (15 points)

ENGSCI 768 - Advanced Operations Research and Analytics (15 points)

STATS 720 - Stochastic Processes (15 points)

STATS 723 - Stochastic Methods: Theory and Applications (15 points)

STATS 783 - Simulation and Monte Carlo Methods (15 points)

COMPSCI 753 - Algorithms for Massive Data (15 points)

COMPSCI 760 - Advanced Topics in Machine Learning (15 points)

COMPSCI 761 - Advanced Topics in Artificial Intelligence (15 points)

COMPSCI 762 - Foundations of Machine Learning (15 points)

ENGSCI 712 - Computational Algorithms for Signal Processing (15 points)

ENGSCI 755 - Decision Making in Engineering (15 points)

OPSMGT 766 - Fundamentals of Supply Chain Coordination (15 points)

SOFTENG 753 - Machine Learning Techniques and Applications (15 points)

STATS 726 - Time Series (15 points)

STATS 731 - Bayesian Inference (15 points)

STATS 763 - Advanced Regression Methodology (15 points)

STATS 769 - Advanced Data Science Practice (15 points)

Up to 30 points may be substituted from approved 600 and 700 level courses offered at this University.

Research Project - 1 Semester

Complete 45 points for ALL of the following:

ENGSCI 795 - Research Project (45 points)

Research Project - 2 Semesters

Complete 45 points for ALL of the following:

ENGSCI 795A - Research Project (15 points)

ENGSCI 795B - Research Project (30 points)