Next Seminar
Comparing Listeners' and Designers' Listening Experiences
04/06/2013 Aalborg University, Nordkraft, Teglgaards Torv, 9000 Aalborg
IIDI News
Workshop on Engaging the Human-Computer Interaction Community With Public Policymaking...
24/05/2013
Invited to co-edit the proceedings of HCI2013, the 27th International British Computer Society...
24/05/2013 Brunel University, 9-13 Spetember, 2013
evolutionary computing
Areas of Expertise
In our increasingly global economy, companies are under pressure to optimise their activities in order to gain a competitive edge or to even remain sustainable. our optimisation research specialises in developing state-of-the-art algorithms that are capable of obtaining solutions to complex...
Projects
The EvoNet Network of Excellence brings together active European researchers and practitioners in the field of evolutionary computing. Originally set up in 1996 with European Commission funding, the EvoNet network provides coordination, support and a web-based infrastructure for research and...
To establish a research infrastructure for realising minute (around 1 cubic millimetre) semiconductor specks which can sense, compute and communicate wirelessly. Specks, scattered or sprayed on the person or surfaces, will collaborate as programmable computational networks called specknets.
A Knowledge Transfer Partnership to use Emergent Computing Techniques for Server Configuration Optimisation
This project seeks to provide the technology and software infrastructure necessary to support the next generation of evolving infohabitants in a way that makes that infrastructure universal, open and scalable. The Distributed Resource Evolutionary Algorithm Machine (DREAM) will use existing...
Tatties is an a system that allows events,for example lectures or tutorials, to be timetabled into timeslots and rooms fully automatically. It uses the new technology of evolutionary algorithms to allow timetables to evolve which not only work, but are "good" from the point of view of all concerned.
The project is concerned with emergence and complexity in socially-inspired artificial systems. We will study large systems consisting of an environment and an inhabitant population. The main goal of the project is to realize an evolving artificial society capable of exploring the environment and...
This is an EU-funded research project to develop basic methodologies and principles of systemic intelligence for artefacts such as robots that will be capable of steadily growing their knowledge through continued experience. The project involves four teams: one in the School of Computing at Napier...
Metaheuristics are widely used to solve important practical combinatorial optimization problems. But the how and why they work effectively for specific problems and for others not, remains a mystery. The overall goal of the Metaheuristis Network is to explore these mysteries, to structure algorithm...
Members
Publications
AlJassani, B.A., Urquhart, N., Almaini, A.E.A. (2010). Manipulation and Optimization techniques for Boolean logic. IET Computers and Digital Techniques , 4(3), 227-239.
Scott, C., Urquhart, N., Hart, E. (2010). Influence of Topology and Payload on CO2 Optimised Vehicle Routing. In: Chio, C. (Ed.) Applications of Evolutionary Computation. Istanbul: Springer Berlin / Heidelberg.
Urquhart, N., Scott, C., Hart, E. (2010). Using an evolutionary algorithm to discover low CO2 tours within a Travelling Salesman Problem. In: al., C. (Ed.) Evo Applications 2010, Part II, LNCS 6025. (pp. 421-430). Springer-Verlag.
Urquhart, N. (2010, January). USING REAL-WORLD GEOSPATIAL DATA WITH EVOLUTIONARY ALGORITHMS. Paper presented at Universities' Transport Study Group, Plymouth, UK.
AlJassani, B.A., Urquhart, N., Almaini, A.E.A. (2009). Minimization of Incompletely Specified Mixed Polarity Reed Muller Functions using Genetic Algorithm. In: Procedings of the 3rd IEEE international conference on Signal Circuits & Systems. Tunisia: IEEE Computer Society Press.
Urquhart, N., Vogogias, T., McEwan, T. (2009, May). CO2Y The Intelligent Green Solution: Minimising Carbon Emissions by Maximising Shared Travel Opportunity. Paper presented at Scottish Transport Applications Research Conference, Glasgow.
Craenen, B., Paechter, B. (2008). A Conflict Tabu Search Evolutionary Algorithm for Solving Constraint Satisfaction Problems. In: Hemert, J., Cotta, C. (Eds.) Evolutionary Computation in Combinatorial Optimization, LNCS 4972. Springer.
Lopez-Ibanez, M., Tumula, P., Paechter, B. (2008). Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks. Journal of Water Resource Planning and Management, 134(4), 337-346.
Lewis, R., Paechter, B., McCollum, B. (2007). Post Enrolment based Course Timetabling: A Description of the Problem Model used for Track Two of the Second International Timetabling Competition.
Urquhart, N. (2007). Carbon Friendly Travel Plan Construction Using an Evolutionary Algorithm. In: Thierens, D., Beyer, H., Bongard, J., Branke, J., Clark, J., Cliff, D., Congdon, C., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J., Moore, J., Neumann, F., Pelikan, M., P, R. (Eds.) GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation. (pp. 2269--2269). London, UK: ACM.
Hart, E., Ross, P., Corne, D. (2005). Evolutionary Scheduling: A Review. Genetic Programming and Evolable Machines, (2), 191-220.
Gottlieb, J., Hart, E., Middendorf, M., Raidl, G., Reeves, C. (Eds.) (2004). Special Issue: Journal of Mathematical Modelling and Algorithms, 3(4).
