Project title Using data analytics to evaluate the efficiency of shipping container movements in Port of Brisbane
Project duration 4 weeks

A collaboration between Port of Brisbane (PoB) and UQ was formed in 2015 to provide PoB with innovative solutions that will future-proof its position as one of Australia's and Queensland's major facilitators of trade and commerce.

A key project under this collaboration aims to develop automated, efficient algorithms for planning drayage operations (moving shipping containers to/from port by truck). As the truck companies currently rely on human expertise for operational planning, algorithms such as this can significantly reduce operational costs to the company and its customers, while also reducing the traffic and pollution from inefficient truck movements. 

The winter research project provides the opportunity for a student to engage in this project through data analytics. The data to be analysed includes three months information of truck trips of a medium-sized transport company to/from Port of Brisbane. The student would be involved in analysing the data and building the appropriate algorithm with the supervisor to assist in answering the research question.

Expected outcomes and deliverables
  • Identify potential missing and/or invalid data 
  • Develop techniques to correct the invalid data
  • Data cleaning
  • Develop insights from the data, to answer research questions such as, but not limited to:
    • Planning efficiency: How often do the trucks perform unnecessary trips (staging); what is the average number of containers on a truck in each route; how often do the trucks have to wait for the container to be ready; how often is the operation performed live?
    • Automation efficiency: what data-input errors exist; when the data is missing; can it be fixed using the existing data?
  • Documentation: in the form of a research paper and presentation of the findings. The results will be used in future research publications.
Suitable for

This project is open to students currently enrolled in any school at UQ, who have completed at least two years of full-time study at UQ. There is no domain knowledge needed relating to the context (freight, shipping container, planning operation, staging, etc.).  

Good programing skills are essential, preferably in Java, Python, or R. Knowledge of Excel pivot tables would be helpful, but not essential. Some experience with academic writing would also be beneficial.

The student will be required to sign a data confidentiality agreement. A desk will be available for the student at the PACE building. Meetings can happen either at St Lucia or PACE campuses.

Primary supervisor Dr Mahboobeh Moghaddam
Further information You are welcome to contact the supervisor to learn more about the project prior to submitting an application. If you are interested, please submit an application.