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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...

Techniques for Auditing the ICT Carbon Footprint of an Organisation

Journal Article
Mouchet, C., Urquhart, N., & Kemmer, R. (2014)
Techniques for Auditing the ICT Carbon Footprint of an Organisation. International Journal of Green Computing, 5(1), 44-61. https://doi.org/10.4018/ijgc.2014010104
This article has presents an extensive survey of the state of the art in Green IT/S. The findings of the survey suggest that there is scope for a reliable carbon footprint aud...

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...

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...

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...

When is bigger better? The effects of group size on the evolution of helping behaviours: Effects of group size on evolution of helping

Journal Article
Powers, S. T., & Lehmann, L. (2017)
When is bigger better? The effects of group size on the evolution of helping behaviours: Effects of group size on evolution of helping. Biological Reviews, 92(2), 902-920. https://doi.org/10.1111/brv.12260
Understanding the evolution of sociality in humans and other species requires understanding how selection on social behaviour varies with group size. However, the effects of g...

A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation

Journal Article
Segredo, E., Seguro, C., Coromoto, L., & Hart, E. (2014)
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-1454-y
In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The...

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 ...

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...