On Constructing Ensembles for Combinatorial Optimisation
Hart, E., & Sim, K. (2018)
On Constructing Ensembles for Combinatorial Optimisation. Evolutionary Computation, 26(1), 67-87. https://doi.org/10.1162/evco_a_00203
Although the use of ensemble methods in machine-learning is ubiquitous due to their proven ability to outperform their constituent algorithms, ensembles of optimisation algori...
Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.
Lopez-Ibanez, M., Tumula, P., & Paechter, B. (2011)
Representations and evolutionary operators for the scheduling of pump operations in water distribution networks. Evolutionary Computation, 19, 429-467. https://doi.org/10.1162/EVCO_a_00035
Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operati...
Setting the research agenda in automated timetabling: the second international timetabling competition
McCollum, B., Schaerf, A., Paechter, B., McMulan, P., Lewis, R. M. R., Parkes, A. J., …Burke, E. (2010)
Setting the research agenda in automated timetabling: the second international timetabling competition. INFORMS Journal on Computing, 22, 120-130. https://doi.org/10.1287/ijoc.1090.0320
The Second International Timetabling Competition (TTC2007) opened in August 2007. Building on the success of the first competition in 2002, this sequel aimed to further develo...
On the comparison of initialisation strategies in differential evolution for large scale optimisation
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018)
On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z
Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works...
Impact of selection methods on the diversity of many-objective Pareto set approximations
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017)
Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science, 112, (844-853). ISSN 1877-0509
Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultane...
Heaven and Hell: visions for pervasive adaptation
Paechter, B., Pitt, J., Serbedzija, N., Michael, K., Willies, J., & Helgason, I. (2011)
Heaven and Hell: visions for pervasive adaptation. Procedia computer science, 7, 81-82. https://doi.org/10.1016/j.procs.2011.12.025
With everyday objects becoming increasingly smart and the “info-sphere” being enriched with nano-sensors and networked to computationally-enabled devices and services, the way...
Cloud computing - the logistic fundament of future networked care
Thuemmler, C. (2010)
Cloud computing - the logistic fundament of future networked care. PublicTechnology.net,
Cloud computing has the potential to revolutionise data management in health care.
The secret life of the immune system: inspiring pervasive systems
Hart, E. (2008)
The secret life of the immune system: inspiring pervasive systems. PerAda Magazine. doi:10.2417/2200911.1837
The immune system performs more than simply defence and exploiting its additional functionality can lead to the design of better pervasive adaptive systems.
Finding feasible timetables using group-based operators.
Lewis, R. M. R. & Paechter, B. (2007)
Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation. 11, 397-413. doi:10.1109/TEVC.2006.885162. ISSN 1089-778X
This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there a...