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24 results

Vehicular Computation Offloading for Industrial Mobile Edge Computing

Journal Article
Zhao, L., Yang, K., Tan, Z., Song, H., Al-Dubai, A., & Zomaya, A. (in press)
Vehicular Computation Offloading for Industrial Mobile Edge Computing. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2021.3059640
Due to the limited local computation resource, industrial vehicular computation requires offloading the computation tasks with time-delay sensitive and complex demands to othe...

Simulating the actions of commuters using a multi-agent system

Journal Article
Urquhart, N., Powers, S., Wall, Z., Fonzone, A., Ge, J., & Polhill, G. (2019)
Simulating the actions of commuters using a multi-agent system. Journal of Artificial Societies and Social Simulation, 22(2), https://doi.org/10.18564/jasss.4007
The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is de...

Use of machine learning techniques to model wind damage to forests

Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

Selection methods and diversity preservation in many-objective evolutionary algorithms

Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018)
Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009
Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two...

On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems

Journal Article
Voß, S., Segredo, E., Lalla-Ruiz, E., Hart, E., & Voss, S. (2018)
On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems. Expert Systems with Applications, 102, 126-142. https://doi.org/10.1016/j.eswa.2018.02.024
Migrating Birds Optimisation (mbo) is a nature-inspired approach which has been shown to be very effective when solving a variety of combinatorial optimisation problems. More ...

Impact of selection methods on the diversity of many-objective Pareto set approximations

Journal Article
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...

On the comparison of initialisation strategies in differential evolution for large scale optimisation

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...

On Constructing Ensembles for Combinatorial Optimisation

Journal Article
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...

Artificial Immunology for Collective Adaptive Systems Design and Implementation

Journal Article
Capodieci, N., Hart, E., & Cabri, G. (2016)
Artificial Immunology for Collective Adaptive Systems Design and Implementation. ACM transactions on autonomous and adaptive systems, 11(2), 1-25. https://doi.org/10.1145/2897372
Distributed autonomous systems consisting of large numbers of components with no central control point need to be able to dynamically adapt their control mechanisms to deal wi...

A hyper-heuristic ensemble method for static job-shop scheduling.

Journal Article
Hart, E., & Sim, K. (2016)
A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conq...