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.

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

CRICOS Code: 00126G
Updated
Tuesday, 30 October 2018 1:46 AM (this date excludes nested assets)
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