PhD scholarship in optimisation and operations research with industrial applications

As data science pervades modern society, companies are now shifting their focus from predictive analytics (when will something happen?) to prescriptive analytics (what should I do?). The prescriptive analytics challenges in industry often relate to scheduling multiple inter-related events in a complex network of systems, aiming to achieve seamless integration so that the right entities are in the right places at the right times. These problems are typically of enormous scale, involving thousands of inter-related variables and constraints and multiple conflicting objectives. Finding an optimal schedule requires developing efficient optimisation algorithms that can handle the enormous dimensions encountered in practice.

This project will focus on developing mathematical optimisation algorithms for a range of industrial applications. The selected PhD candidate will be embedded within a team of applied mathematicians who have extensive experience working with industry. In the past several years, the team has worked with a range of industry partners across the agriculture, mining, oil and gas, and manufacturing sectors. Some of the team’s prior work includes:

• Optimising vessel schedules and deliveries in offshore oil and gas projects;
• Optimising the timing and sequence of thousands of maintenance activities in mine plants;
• Optimising harvest logistics for grain growers to minimise the combination of storage, shipping, and handling fees; and
• Optimising vehicle use in large vehicle fleets to minimise the combination of capital and maintenance costs subject to minimum distance requirements.

This PhD project will involve further developing the mathematical theory and optimisation algorithms underpinning these applications. The project is part of Professor Ryan Loxton’s ARC Future Fellowship project.

Please submit your CV, Academic Transcripts and a 500 word Expression of Interest detailing why you are interested in being part of this project and how your skills and experience will be beneficial to the project scope to Professor Ryan Loxton, [Email Address Removed]