Study level

  • Vacation research experience scheme


Topic status

We're looking for students to study this topic.

Research centre


Associate Professor Paul Corry
Associate Professor in Operations Research
Division / Faculty
Faculty of Science


Discrete-event-simulation (DES) is a dynamic modelling technique commonly applied in areas of mining, manufacturing, services sector, transport, logistics, supply-chains and healthcare, to name a few. It provides a computerised representation of a real or proposed system which can be analysed, tested and optimised through what-if analysis. Simpy is a freely available Python package which is superior to many expensive commercially available DES software packages in terms of its flexibility to model very complex systems, and to integrate seamlessly with a multitude of powerful Python packages such as Pandas and Numpy. One shortcoming of Simpy is the lack of an integrated animation capability, which most commercial DES software packages include and is very useful for visualising system behaviour, identifying potential bugs in the simulation, highlighting system bottlenecks and aiding in insight and understanding of emergent system behaviours. An Excel based DES animation platform has been developed at QUT to address this short-coming of Simpy.

Research activities

This project aims to use Simpy to model a real-world system (to be determined), and animate the model using the QUT developed Excel platform. This will involve research into the identified real-world system to characterise its behaviour, develop an associated parameter set based on real-world data and/or assumptions, development of Simpy model in Python integrated with the Excel animation platform, and finally testing, analysing and demonstrating the developed simulation model and animation.


The objectives of the project are to demonstrate animation of a Simpy model, test and identify improvements in the animation platform, and use the animation to identify key behaviours and bottlenecks of the system being modelled.

Skills and experience

Basic knowledge of Python and the Discrete-Event-Simulation package SimPy (covered in MXB334 - Operations Research for Stochastic Processes)


You may be eligible to apply for a research scholarship.

Explore our research scholarships



Contact the supervisor for more information.