Selection methods and diversity preservation in many-objective evolutionary algorithms (2018)
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 main tasks simultaneously. First, it has to promote convergence by selecti... Read More about Selection methods and diversity preservation in many-objective evolutionary algorithms.

On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018, September). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. Presented at Fifteenth International Conference on Parallel Problem Solving from Nature (PPSN XV), Coimbra, Portugal

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains, there is a lack of available heuristics, while for novel problems, no heur... Read More about On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains.

Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018, April). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. Presented at 21st International Conference, EvoApplications 2018, Parma, Italy

In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heuristics often suffice in this case. However, for many domains, a simple heurist... Read More about Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs.

On Constructing Ensembles for Combinatorial Optimisation (2017)
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 algorithms have received relatively little attention. Existing approaches lag beh... Read More about On Constructing Ensembles for Combinatorial Optimisation.

A research agenda for metaheuristic standardization. (2015)
Presentation / Conference Contribution
Hart, E., & Sim, K. (2015, June). A research agenda for metaheuristic standardization. Paper presented at 11th Metaheuristics International Conference

We propose that the development of standardized, explicit, machine-readable descriptions of metaheuris- tics will greatly advance scientific progress in the field. In particular, we advocate a purely functional description of metaheuristics — separat... Read More about A research agenda for metaheuristic standardization..

Biological Networks (2011)
Book Chapter
Hart, E. (2011). Biological Networks. In M. Gargaud, R. Amils, J. Quintanilla, & H. Irvine (Eds.), Encyclopedia of Astrobiology (179-182). Springer. https://doi.org/10.1007/978-3-642-11274-4_178

How affinity influences tolerance in an idiotypic network. (2007)
Journal Article
Hart, E., Bersini, H., & Santos, F. (2007). How affinity influences tolerance in an idiotypic network. Journal of Theoretical Biology, 249, 422-436. https://doi.org/10.1016/j.jtbi.2007.07.019

The mutability of bacteriophages offers a particular advantage in the treatment of bacterial infections not afforded by other antimicrobial therapies. When phage-resistant bacteria emerge, mutation may generate phage capable of exploiting and thus li... Read More about How affinity influences tolerance in an idiotypic network..

Evolutionary scheduling: a review. (2005)
Journal Article
Hart, E., Ross, P., & Corne, D. (2005). Evolutionary scheduling: a review. Genetic Programming and Evolvable Machines, 6, 191-220. https://doi.org/10.1007/s10710-005-7580-7

Early and seminal work which applied evolutionary computing methods to scheduling problems from 1985 onwards laid a strong and exciting foundation for the work which has been reported over the past decade or so. A survey of the current state-of-the-a... Read More about Evolutionary scheduling: a review..

Exploiting the analogy between the immune system and sparse distributed memory. (2003)
Journal Article
Hart, E., & Ross, P. (2003). Exploiting the analogy between the immune system and sparse distributed memory. Genetic Programming and Evolvable Machines, 4(4), 333-358. https://doi.org/10.1023/a%3A1026191011609

The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for clustering non-stationary data based on a combination of salient features... Read More about Exploiting the analogy between the immune system and sparse distributed memory..

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002, July). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. Presented at Genetic and Evolutionary Computation Conference (GECCO)

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We
try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..

A heuristic combination method for solving job-shop scheduling problems. (1998)
Presentation / Conference Contribution
Hart, E., & Ross, P. (1998, September). A heuristic combination method for solving job-shop scheduling problems

This paper describes a heuristic combination based genetic algorithm, (GA), for tackling dynamic job-shop scheduling problems. Our approach is novel in that the genome encodes a choice of algorithm to be used to produce a set of schedulable operation... Read More about A heuristic combination method for solving job-shop scheduling problems..