Using MAP-Elites to support policy making around Workforce Scheduling and Routing
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 arc...
Being a leader or being the leader: The evolution of institutionalised hierarchy
Conference Proceeding
Perret, C., Hart, E., & Powers, S. T. (2019)
Being a leader or being the leader: The evolution of institutionalised hierarchy. In ALIFE 2019: The 2019 Conference on Artificial Life, (171-178). https://doi.org/10.1162/isal_a_00158
Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their pe...
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World
Conference Proceeding
Hale, M. F., Buchanan, E., Winfield, A. F., Timmis, J., Hart, E., Eiben, A. E., …Tyrrell, A. M. (2019)
The ARE Robot Fabricator: How to (Re)produce Robots that Can Evolve in the Real World. In ALIFE 2019: The 2019 Conference on Artificial Life, 95-102. https://doi.org/10.1162/isal_a_00147
The long term vision of the Autonomous Robot Evolution (ARE) project is to create an ecosystem of both virtual and physical robots with evolving brains and bodies. One of the ...
Algorithm selection using deep learning without feature extraction
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 ...
An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem
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 addr...
Evolving robust policies for community energy system management
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 p...
Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem.
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 ...
Use of machine learning techniques to model wind damage to forests
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 r...
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...
On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains
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 Ihttps://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,...