University College Cork, Ireland, founded in 1845, is one of Ireland’s leading research institutions, and offers over 120 different degrees and professional programmes across the areas of Science and Engineering, Business, Medicine, Law, Humanities and Social Science. Today the University has over 18000 students and 2500 staff. In 2011, UCC became the first university worldwide to achieve the ISO 50001 standard in energy management. Within UCC, Logistar is hosted in the Insight lab in the School of Computer Science, which has a long standing track record of research and innovation in artificial intelligence and its applications. The founder of the lab, Professor Eugene Freuder, is the 2020 winner of the IJCAI Award for Research Excellence, for his foundational work in Constraint Programming, which has significant application in the areas of scheduling routing and resource allocation. The current lab director, Professor Barry O’Sullivan, is the President of EurAI, the European Association for Artificial Intelligence.
Insight, the SFI Research Centre for Data Analytics, is a national research centre distributed across seven universities, funded by Science Foundation Ireland. Since its creation in 2013, Insight has been a partner in over 90 European research projects, has signed 72 industrial licence agreements for its technology, has created 11 spin out companies, and has 121 collaborative research agreements with 89 industry partners. Fundamentally, Insight is about transforming lives, businesses and society by empowering better decisions. We do this by advancing the state of the art in Machine Learning, Artificial Intelligence and related disciplines to unlock knowledge from raw data.
UCC Computer Science also participates in Confirm, the SFI centre for smart manufacturing, where it conducts research in the application of AI to manufacturing, logistics and supply chains, with multiple industry partners.
In Logistar, UCC’s role is to apply its expertise in Artificial Intelligence to the prediction of events, delays and disruptions in logistics operations, and to the modelling of the preferences of the different actors in the logistics chains. We work with the industry partners and stakeholders to analyse data on deliveries and shipments between factories, distribution centres and customer sites across multimodal transport networks. We use the data streams created and collated by the other partners in order to predict arrival times at different destinations, turnaround times at customer sites, expected delays in transport networks, and potential future co-loading and backloading collaboration opportunities. Further, through collaboration with the stakeholders, we build models of decision-maker preferences for logistics management. We make these models available in Logistar for use by systems which optimise logistics schedules and for automated negotiation of collaborative working when schedules change unexpectedly or when new opportunities arise.
Through our work in Logistar, we expect to develop novel software systems for automated prediction in support of logistics services that can be exploited by our partner companies and further developed by the research community. In addition, by collaborating closely with leading companies in the European logistics space, we hope to develop challenging application problems for our scientific research, which will guide our future research directions.