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All Outputs (16)

Accelerating neural network architecture search using multi-GPU high-performance computing (2022)
Journal Article
Lupión, M., Cruz, N. C., Sanjuan, J. F., Paechter, B., & Ortigosa, P. M. (2023). Accelerating neural network architecture search using multi-GPU high-performance computing. Journal of Supercomputing, 79, 7609-7625. https://doi.org/10.1007/s11227-022-04960-z

Neural networks stand out from artificial intelligence because they can complete challenging tasks, such as image classification. However, designing a neural network for a particular problem requires experience and tedious trial and error. Automating... Read More about Accelerating neural network architecture search using multi-GPU high-performance computing.

Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes (2019)
Journal Article
Ferrández, M. R., Redondo, J. L., Ivorra, B., Ramos, A. M., Ortigosa, P. M., & Paechter, B. (2020). Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes. Engineering Optimization, 52(5), 896-913. https://doi.org/10.1080/0305215x.2019.1618289

This work focuses on the optimization of some high-pressure and temperature food treatments. In some cases, when dealing with real-life multi-objective optimization problems, such as the one considered here, the computational cost of evaluating the c... Read More about Improving the performance of a preference-based multi-objective algorithm to optimize food treatment processes.

On the comparison of initialisation strategies in differential evolution for large scale optimisation (2017)
Journal Article
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 have studied the effects that a population initialisation strategy has on... Read More about On the comparison of initialisation strategies in differential evolution for large scale optimisation.

A Lifelong Learning Hyper-heuristic Method for Bin Packing (2015)
Journal Article
Hart, E., Sim, K., & Paechter, B. (2015). A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121

We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; representative problems and heur... Read More about A Lifelong Learning Hyper-heuristic Method for Bin Packing.

This pervasive day: creative Interactive methods for encouraging public engagement with FET research (2011)
Journal Article
Helgason, I., Bradley, J., Egan, C., Paechter, B., & Hart, E. (2011). This pervasive day: creative Interactive methods for encouraging public engagement with FET research. Procedia Computer Science, 7, 207-208. https://doi.org/10.1016/j.procs.2011.09.028

This paper describes a case study of a programme of interactive public engagement activities presented by the PerAda Co-ordination Action project (FET Proactive Initiative on Pervasive Adaptation) [1] in 2011. The intention behind these events was to... Read More about This pervasive day: creative Interactive methods for encouraging public engagement with FET research.

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks. (2011)
Journal Article
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 operations of pumps. Schedules can be defined either implicitly, in terms of other... Read More about Representations and evolutionary operators for the scheduling of pump operations in water distribution networks..

Heaven and Hell: visions for pervasive adaptation (2011)
Journal Article
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 we interact with our environment has changed significantly, and will conti... Read More about Heaven and Hell: visions for pervasive adaptation.

Setting the research agenda in automated timetabling: the second international timetabling competition (2009)
Journal Article
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 develop research activity in the area of educational timetabling. The broad aim o... Read More about Setting the research agenda in automated timetabling: the second international timetabling competition.

Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks (2008)
Journal Article
López-Ibáñez, M., Prasad, T. D., & Paechter, B. (2008). Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks. Journal of Water Resources Planning and Management, 134, 337-346. https://doi.org/10.1061/%28ASCE%290733-9496%282008%29134%3A4%28337%29

Reducing energy consumption of water distribution networks has never had more significance than today. The greatest energy savings can be obtained by careful scheduling of operation of pumps. Schedules can be defined either implicitly, in terms of ot... Read More about Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks.

Finding feasible timetables using group-based operators. (2007)
Journal Article
Lewis, R. M. R., & Paechter, B. (2007). Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation, 11, 397-413. https://doi.org/10.1109/TEVC.2006.885162

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 are, in fact, various scaling up issues surrounding this sort of algorithm a... Read More about Finding feasible timetables using group-based operators..

A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS (2006)
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2007). A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS. Journal of Mathematical Modelling and Algorithms, 6(2), 213-230. https://doi.org/10.1007/s10852-006-9041-6

Real optimization problems often involve not one, but multiple objectives, usually in conflict. In single-objective optimization there exists a global optimum, while in the multi-objective case no optimal solution is clearly defined but rather a set... Read More about A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS.

Parallelization of population-based multi-objective meta-heuristics: An empirical study (2005)
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2006). Parallelization of population-based multi-objective meta-heuristics: An empirical study. Applied Mathematical Modelling, 30(7), 578-592. https://doi.org/10.1016/j.apm.2005.05.021

In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of pro... Read More about Parallelization of population-based multi-objective meta-heuristics: An empirical study.

PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation (2004)
Journal Article
de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B., & Martin, J. M. (2004). PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing, 30(5-6), 721-739. https://doi.org/10.1016/j.parco.2003.12.012

This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisation problems. We propose a new algorithm called PSFGA (parallel single fron... Read More about PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation.

A scaleable and robust framework for distributed application. (2002)
Journal Article
Jelasity, M., Preuss, M., & Paechter, B. (2002). A scaleable and robust framework for distributed application. World Congress on Computational Intelligence, 2, 1540-1545

This paper describes a novel tool for running distributed experiments on the Internet. The possible applications include simple load balancing, parallel evolutionary computation, agent-based simulation and artificial life. Our environment is based on... Read More about A scaleable and robust framework for distributed application..

Maintaining connectivity in a scaleable and robust distributed environment. (2002)
Journal Article
Jelasity, M., Preuss, M., Van Steen, M., & Paechter, B. (2002). Maintaining connectivity in a scaleable and robust distributed environment. Cluster Computing and the Grid, 389-394. https://doi.org/10.1109/CCGRID.2002.1017166

This paper describes a novel peer-to-peer (P2P) environment for running distributed Java applications on the Internet. The possible application areas include simple load balancing, parallel evolutionary computation, agent-based simulation and artific... Read More about Maintaining connectivity in a scaleable and robust distributed environment..