All Outputs (188)

A novel similarity-based mutant vector generation strategy for differential evolution (2018)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018, July). A novel similarity-based mutant vector generation strategy for differential evolution. Presented at The Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Kyoto, Japan

The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the search space. However, it is also responsible for promoting intensificatio... Read More about A novel similarity-based mutant vector generation strategy for differential evolution.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Presentation / Conference Contribution
Hart, E., Steyven, A. S. W., & Paechter, B. (2018, July). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. Presented at GECCO 2018, Kyoto, Japan

The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad range of studies that includes insect groups, human groups and swarm robot... Read More about Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm.

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 the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems (2018)
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 recently, an adaptation of the algorithm has been proposed that enables it... Read More about On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems.

For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems (2017)
Presentation / Conference Contribution
Pitt, J., & Hart, E. (2017, September). For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems. Presented at 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W)

This position paper is concerned with the challenge of engineering multi-scale and long-lasting systems, whose operation is regulated by sets of mutually-agreed, conventional rules. The core of the problem is that there are multiple, inter-dependent... Read More about For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems.

Impact of selection methods on the diversity of many-objective Pareto set approximations (2017)
Presentation / Conference Contribution
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017, September). Impact of selection methods on the diversity of many-objective Pareto set approximations. Presented at 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Marseille, France

Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultaneously. First of all, they must select individuals that are as close as poss... Read More about Impact of selection methods on the diversity of many-objective Pareto set approximations.

Emergence of hierarchy from the evolution of individual influence in an agent-based model (2017)
Presentation / Conference Contribution
Perret, C., Powers, S. T., & Hart, E. (2017, September). Emergence of hierarchy from the evolution of individual influence in an agent-based model. Presented at 14th European Conference on Artificial Life (ECAL 2017)

The sudden transition from egalitarian groups to hierarchical societies that occurred with the origin of agriculture is one of the most striking features of the evolution of human societies. Hierarchy is reflected by the evolution of an asymmetrical... Read More about Emergence of hierarchy from the evolution of individual influence in an agent-based model.

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector (2017)
Presentation / Conference Contribution
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017, July). A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. Presented at Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '17

Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing risk assessment methods is thus one of the keys to finding forest management... Read More about A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector.

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.

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics (2017)
Presentation / Conference Contribution
Steyven, A., Hart, E., & Paechter, B. (2017, July). An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. Presented at Genetic and Evolutionary Computation Conference - GECCO '17

A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. However, the role played by the environment in influencing the effectiveness o... Read More about An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics.

Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation (2016)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016, May). Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. Presented at Learning and Intelligent OptimizatioN Conference LION 10, Ischia Island (Napoli), Italy

Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic which can apply one of two meta-heuristics at the current stage of the search.... Read More about Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation.

Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems (2016)
Presentation / Conference Contribution
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016, July). Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. Presented at IEEE World Congress on Computational Intelligence

In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control scheme based on both Fuzzy Logic Controllers (FLCs) and Hyper-heuristics (HHs).... Read More about Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems.

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems (2016)
Presentation / Conference Contribution
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016, September). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. Presented at 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016)

We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), t... Read More about Analysing the performance of migrating birds optimisation approaches for large scale continuous problems.

Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm (2016)
Presentation / Conference Contribution
Steyven, A., Hart, E., & Paechter, B. (2016, October). Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. Presented at PPSN 2016 14th International Conference on Parallel Problem Solving from Nature

It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear exactly how parameterisation of a given environment might influence the emer... Read More about Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm.

Artificial Immunology for Collective Adaptive Systems Design and Implementation (2016)
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 with an unpredictable and changing environment. Existing frameworks for engin... Read More about Artificial Immunology for Collective Adaptive Systems Design and Implementation.

A hyper-heuristic ensemble method for static job-shop scheduling. (2016)
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-conquer approach in which each heuristic solves a unique subset of the instance... Read More about A hyper-heuristic ensemble method for static job-shop scheduling..

Roll Project Bin Packing Benchmark Problems. (2015)
Data
Hart, E., & Sim, K. (2015). Roll Project Bin Packing Benchmark Problems. [Data]. https://doi.org/10.17869/ENU.2015.9364

This document describes two sets of Benchmark Problem Instances for the One Dimensional Bin Packing Problem. The problem instances are supplied as compressed (zipped) SQLITE database files.

A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules (2015)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2015, July). A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules. Presented at Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15

A previously described hyper-heuristic framework named
NELLI is adapted for the classic Job Shop Scheduling Problem (JSSP) and used to find ensembles of reusable heuristics that cooperate to cover the heuristic search space. A new heuristic generato... Read More about A Novel Heuristic Generator for JSSP Using a Tree-Based Representation of Dispatching Rules.

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. (2015)
Presentation / Conference Contribution
Hart, E., Steyven, A., & Paechter, B. (2015, July). Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. Presented at Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15

Ensuring the integrity of a robot swarm in terms of maintaining
a stable population of functioning robots over long
periods of time is a mandatory prerequisite for building more
complex systems that achieve user-defined tasks. mEDEA
is an environ... Read More about Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication..

Grid diversity operator for some population-based optimization algorithms. (2015)
Presentation / Conference Contribution
Salah, A., & Hart, E. (2015, July). Grid diversity operator for some population-based optimization algorithms. Presented at GECCO’15 Companion

We present a novel diversity method named Grid Diversity
Operator (GDO) that can be incorporated into multiple
population-based optimization algorithms that guides the
containing algorithm in creating new individuals in sparsely
visited areas of... Read More about Grid diversity operator for some population-based optimization algorithms..