Using MAP-Elites to support policy making around Workforce Scheduling and Routing (2020)
Journal Article
Urquhart, N., Hart, E., & Hutcheson, W. (2020). Using MAP-Elites to support policy making around Workforce Scheduling and Routing. Automatisierungstechnik, 68(2), https://doi.org/10.1515/auto-2019-0107

English abstract: Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be use... Read More about Using MAP-Elites to support policy making around Workforce Scheduling and Routing.

Evolving robust policies for community energy system management (2019)
Conference Proceeding
Cardoso, R., Hart, E., & Pitt, J. (2019). Evolving robust policies for community energy system management. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1120-1128). https://doi.org/10.1145/3321707.3321763

Community energy systems (CESs) are shared energy systems in which multiple communities generate and consume energy from renewable resources. At regular time intervals, each participating community decides whether to self-supply, store, trade, or sel... Read More about Evolving robust policies for community energy system management.

Algorithm selection using deep learning without feature extraction (2019)
Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019). Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (198-206). https://doi.org/10.1145/3321707.3321845

We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In contrast to the majority of work in algorithm-selection, the approach does... Read More about Algorithm selection using deep learning without feature extraction.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Conference Proceeding
Urquhart, N., Hoehl, S., & Hart, E. (2019). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1347-1355). https://doi.org/10.1145/3321707.3321767

An increasing emphasis on reducing pollution and congestion in city centres combined with an increase in online shopping is changing the ways in which logistics companies address vehicle routing problems (VRP). We introduce the {\em micro-depot}-VRP,... Read More about An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem.

Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. (2019)
Conference Proceeding
Urquhart, N., Hart, E., & Hutcheson, W. (2019). Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. In EvoApplications 2019: Applications of Evolutionary Computation (49-63). https://doi.org/10.1007/978-3-030-16692-2_4

Quality-diversity algorithms such as MAP-Elites provide a means of supporting the users when finding and choosing solutions to a problem by returning a set of solutions which are diverse according to set of user-defined features. The number of soluti... Read More about Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem..

Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments (2018)
Conference Proceeding
Cardoso, R. P., Rossetti, R. J. F., Hart, E., Kurka, D. B., & Pitt, J. (2018). Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments. In T. Margaria, & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Distributed Systems (221-240). https://doi.org/10.1007/978-3-030-03424-5_15

Electronic institutions are socially-inspired multi-agent systems, typically operating under a set of policies, which are required to determine system operation and to deal with violations and other non-compliant behaviour. They are often faced with... Read More about Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments.

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)
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part I. https://doi.org/10.1007/978-3-319-99253-2_14

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.

Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites (2018)
Conference Proceeding
Urquhart, N., & Hart, E. (2018). Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites. In Parallel Problem Solving from Nature – PPSN XV 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part I. https://doi.org/10.1007/978-3-319-99253-2_39

Workforce Scheduling and Routing Problems (WSRP) are very common in many practical domains, and usually have a number of objectives. Illumination algorithms such as Map-Elites (ME) have recently gained traction in application to design problems, in p... Read More about Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites.

Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism (2018)
Conference Proceeding
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018). Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. In T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki, & H. Iizuka (Eds.), Proceedings of the 2018 Conference on Artificial Life. https://doi.org/10.1162/isal_a_00058

Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders' decisions by aggregating their own and their neighbours' experience, and i... Read More about Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism.

A new rich vehicle routing problem model and benchmark resource (2018)
Conference Proceeding
Sim, K., Hart, E., Urquhart, N. B., & Pigden, T. (2018). A new rich vehicle routing problem model and benchmark resource. In Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. https://doi.org/10.1007/978-3-319-89988-6_30

We describe a new rich VRP model that captures many real-world constraints, following a recently proposed taxonomy that addresses both scenario and problem physical characteristics. The model is used to generate 4800 new instances of rich VRPs which... Read More about A new rich vehicle routing problem model and benchmark resource.

Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm (2018)
Conference Proceeding
Hart, E., Steyven, A. S. W., & Paechter, B. (2018). Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. In GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference (101-108). https://doi.org/10.1145/3205455.3205481

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.

A novel similarity-based mutant vector generation strategy for differential evolution (2018)
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018). A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018. https://doi.org/10.1145/3205455.3205628

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.

Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs (2018)
Conference Proceeding
Stone, C., Hart, E., & Paechter, B. (2018). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. In Applications of Evolutionary Computation (578-593). https://doi.org/10.1007/978-3-319-77538-8_40

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)
Conference Proceeding
Pitt, J., & Hart, E. (2017). For Flux Sake: The Confluence of Socially- and Biologically-Inspired Computing for Engineering Change in Open Systems. In 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W),. https://doi.org/10.1109/fas-w.2017.119

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)
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. https://doi.org/10.1016/j.procs.2017.08.077

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.

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector (2017)
Conference Proceeding
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017). A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (1121-1128). https://doi.org/10.1145/3071178.3071217

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)
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2017). An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (155-162). https://doi.org/10.1145/3071178.3071232

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.