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IN THE SPOTLIGHT 

Hoa Bui attended AustMS meeting at the University of Queensland. Her trip was funded by the GSOP 2023 Grant Development Funding.

She shared her exciting research on new fast and exact algorithms to solve a classical facility locations problem. 

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Hoa sharing her research at the University of Queensland

Sandy Spiers and Ponpot Jartnillaphand attended and presented their research at the WOMBAT/WICO conference in Sydney 11-15 December 2023.

In 2023, the annual Workshop on Optimisation, Metric Bounds, Approximation and Transversality (WOMBAT 2023) was run in conjunction with the second biennial Workshop on the Intersections of Computation and Optimisation (WICO 2023). Together, these workshops brought together Australian and international researchers interested in all areas of optimisation and computational mathematics.

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Ponpot presenting Parallel Machine Scheduling Problem with Flexible Resourced and Shift Consideration the WOMBAT conference

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Tyler Bikaun presented: MaintIE: A Fine-Grained Annotation Schema and Benchmark for Information Extraction from Maintenance Short Texts

Maintenance short texts (MST) are value resources for asset management as they offer insights into the condition and maintenance of machines and infrastructure. However, extracting and using this information efficiently on a large scale can be challenging.

Tyler introduced "MaintIE," a novel multi-level annotation scheme designed for entity recognition and relation extraction within MST, in this presentation. This scheme categorises information into five primary classes -

Physical Object, State, Process, Activity, and Property - and further breaks them into 224 specific entities. Additionally, it includes six relations tailored to the context of MST.

Tyler

outlined the creation of two corpora using MaintIE. The first is a meticulously annotated corpus of 1,076 texts characterised by its high quality and fine-grained detail. The second is a larger, coarse-grained corpus comprising 7,000 texts, which has been instrumental in enhancing the capabilities of fine-grained information extraction.

Tyler explored the performance of various deep-learning models using these corpora, setting benchmarks for automated entity recognition and relation extraction in MST

and demonstrated how the MaintIE scheme, corpus, and models can be adopted by industry through their public release made available under the MIT license to foster further research and innovation in this domain.

Hoa Bui presents - Maintenance scheduling optimisation in the resources and energy industry

In academic literature, maintenance scheduling optimisation is often seen as a

resource-constrained project scheduling problem, a topic studied extensively since the late 1950s. However, existing mathematical models and solution methods, including exact, heuristic, and meta-heuristic approaches, are

only partially suited for the unique challenges of real-world scheduling problems in the resources and energy industry, characterised by their large-scale and tight constraints.

In this presentation, 

Hoa gave a general picture

of how researchers at the Optimisation Theme at ITTC are working to bridge these gaps and develop practical solutions for optimising maintenance schedules for our industry partners.