Ed Keedwell, Professor of Artificial Intelligence (AI) in the Computer Science department at the University of Exeter, has joined CFCM with two of his latest projects on transport optimisation. Prof Keedwell brings with him over 15 years of research in AI and a wealth of expertise in optimisation (e.g. genetic algorithms, swarm intelligence, hyperheuristics) machine learning and AI-based simulation. He leads a research group focusing on applied Artificial Intelligence and his main research interests are the optimisation of transportation systems, and the development of sequence-based hyperheuristics and human-in-the-loop optimisation methods for applications in engineering.
Over the last two years, Prof Keedwell has established a strong partnership with City Science, a Devon-based tech company, which specialises in the optimisation of urban systems, especially with regard to transport and energy modelling. The team at City Science work closely with other organisations to provide insights, develop new fit-for-purpose solutions, identify efficiency opportunities and inform policy options – all with the aim of making cities fit for the demands of modern living.
The partnership between City Science and the University of Exeter was sparked through the Impact Lab in early 2018. Since that first award-winning project, Exeter and City Science have worked together on 7 projects, leveraging nearly £2 million in UK government funding.
Two recent projects focus on transport optimisation:
Knowledge Transfer Partnership
The aim of this project is to develop metaheuristic (e.g. evolutionary algorithms) and hyper-heuristic optimisation approaches to solve the emerging Dual Problem of simultaneous optimisation across both transport and energy networks. The work will be undertaken by a Knowledge Transfer Associate, who is currently being recruited, with the assistance of Prof Keedwell and the team at City Science.
Real-Time Distributed Optimisation of Dualed Transport & Electrical Networks
The aim of this project is to develop a fully integrated, real-time transport electric-hydrogen network simulation and optimisation engine to deliver the most cost-effective planning and operation of new transport-integrated electrical/hydrogen systems. The team will investigate existing simulation and optimisation approaches to both transportation and energy network planning, identifying and developing appropriate simulation and optimisation methods.
We are very happy and proud to welcome Prof Keedwell in our team and look forward to many more future projects aimed at making transport cleaner and more efficient.
If you are interested in Professor Keedwell’s research and would like to get in contact, please send us an email at email@example.com.