Real-time optimisation, scheduling and logistics

Pioneering optimisation solutions for remote engineering

Intelligent automation technologies are critical for remote engineering projects. They route vehicles, control storage, schedule labour and resources, organise maintenance and respond to unforeseen events.

This group’s research develops optimisation, scheduling and control solutions for the mining and offshore extraction sectors and associated operations, such as transport, energy supply and the servicing of remote communities.

With a strong focus on real-time optimisation, this group devises new ways for work plans and models to be rapidly adapted as needed.

PhD Opportunities

To find out more about our PhD opportunities, please contact the project lead.
Real-time Optimisation in Operations of Transport, Mining and Energy

Project description:

Real-time optimisation and scheduling is a challenging task in developing intelligent automation technologies. Its implementation can be in the shape of routing vehicles, controlling storage, scheduling labour, organising maintenance, allocating resources and responding to unforeseen events.

The major Western Australian industries collaborate with The University of Western Australia in this area are in following sectors: transport, energy supply, servicing remote communities, mining and offshore extraction.

The focus of research in this area is to devise new state of the art strategies for work plans and models to be rapidly adapted as needed.

PhD Applicant Eligibility Criteria:

Applicants are required to meet the standard admissions requirements as determined by the Graduate Research School.

Project Lead Contact details:

Dr Ghulam Mubashar Hassan


Email: [email protected]

Group projects

  • Optimisation of road work maintenance scheduling
  • Pavement deterioration model for optimising road maintenance scheduling
  • Correlation of FWD, TSD and road imaging survey data for road maintenance scheduling optimisation
  • Seasonal adjustment factor for road survey data
  • Machine learning for optimisation of port operations
  • Simulating autonomous vehicles
  • Traffic visualisation
  • Ship scheduling for the North-West Shelf
  • Business process automation
  • Tabletop traffic simulation
  • Truck shop scheduling
  • Ore body visualisation
  • Approximate methods for optimising timed processes
  • Market based optimisation for the vehicle routing problem
  • Mine plan optimisation

Research opportunities are available for students. To submit an expression of interest for a research opportunity, fill out our form or email.

Contact Research Cluster Lead Professor Andy Fourie