Outputs (12)

Use of machine learning techniques to model wind damage to forests (2018)
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 risk of damage in storms. Models based on these techniques were developed i... Read More about Use of machine learning techniques to model wind damage to forests.

Engineering Sustainable and Adaptive Systems in Dynamic and Unpredictable Environments (2018)
Presentation / Conference Contribution
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, Verifica

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)
Presentation / Conference Contribution
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 8–1

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)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2018, September). Optimisation and Illumination of a Real-world Workforce Scheduling and Routing Application via Map-Elites. Presented at Parallel Problem Solving from Nature (PPSN) 2018, Coimbra, Portugal

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)
Presentation / Conference Contribution
Perret, C., Powers, S. T., Pitt, J., & Hart, E. (2018, July). Can justice be fair when it is blind? How social network structures can promote or prevent the evolution of despotism. Presented at The 2018 Conference on Artificial Life, Tokyo, Japan

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)
Presentation / Conference Contribution
Sim, K., Hart, E., Urquhart, N. B., & Pigden, T. (2015, September). A new rich vehicle routing problem model and benchmark resource. Presented at International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with

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.

Creating optimised employee travel plans (2018)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2015, September). Creating optimised employee travel plans. Presented at EuroGen 2015

The routing of employees who provide services such as home health or social care is a complex problem. When sending an employee between two addresses , there may exist more than one travel option, e.g. public transport or car. In this paper we examin... Read More about Creating optimised employee travel plans.

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.