The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence. The group has an excellent international reputation: it will host the 14th International Conference on Parallel Problem Solving from Nature in Edinburgh in 2016, with Prof. Emma Hart and Prof. Ben Paechter as General Chairs. The group inaugurated the international EvoStar Conference in 1998 and has run the conference since then, overseeing its growth into 4 co-located conferences. Staff regularly chair tracks at GECCO and ALife. Prof. Hart and Prof. Paechter are Associate Editors of the Evolutionary Computation Journal (MIT Press). The group has a sustained record of attracting funding from both international (EU) and national funding bodies, including EPSRC and Leverhulme. We have an excellent record of encouraging collaborative working with other researchers both in the UK and worldwide, for example hosting visiting international PhD students and visiting researchers, and writing joint publications with external authors.
The group has a particular interest in application of nature-inspired techniques to practical optimisation where we have a track record of working with industry. Current projects include use of evolution in design, optimisation of cutting patterns in the Forestry Industry, scheduling in the Health Care sector, and vehicle routing, with a specific emphasis on reducing carbon emissions, (working in conjunction with Edinburgh Napier’s Transport Research Institute). However, we also conduct fundamental research with the goal of improving understanding of bio-inspired optimisation and learning algorithms, for example covering evolutionary robotics, evolution of societies and the hybridisation of machine-learning and optimisation.
Hart, E., Sim, K., Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23, (1), 37-67.
Hart, E., Steyven, A., Paechter, B. (2015). Improving Survivability in Environment-driven Distributed Evolutionary Algorithms through Explicit Relative Fitness and Fitness Proportionate Communication. In: Silva, S. (Ed.) Proceedings of GECCO '15: 2015 Genetic and Evolutionary Computation Conference, , () ( ed.). (pp. ). Madrid, Spain: . ACM SIGEVO.
Hart, E., Sim, K. (2015, ). A Research Agenda for Metaheuristic Standardization. Paper presented at 11th Metaheuristics International Conference, Agadir.
Steyven, A., Hart, E., Paechter, B. (2016). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In: Handl, J., Hart, E., Lewis, Peter R., Lopez-Ibanez, M., Ochoa, G., Paechter, B. (Eds.) Parallel Problem Solving from Nature – PPSN XIV, , () ( ed.). (pp. ). : . Springer International Publishing.
Martí, L., Segredo, E., Sanchez-Pi, N., Hart, E. (2017). Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science 00 (2017) 000–000 21st International Conference on Knowledge Based and Intelligent Information and Engineering Systems, , (In press), 1-10.
Urquhart, N. (2015). Optimising the scheduling and planning of urban milk deliveries. In: Mora, A., Squillero, G. (Eds.) Lecture Notes in Computer Science, 9028, () ( ed.). (pp. 604-615). : . Springer International Publishing.