Outputs (59)

Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language (2024)
Presentation / Conference Contribution
Urquhart, N., & Hunter, K. (2024, April). Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language. Presented at 27th European Conference, EvoApplications 2024, Aberystwyth, UK

When using a meta-heuristic based optimiser in some industrial scenarios, there may be a need to amend the objective function as time progresses to encompass constraints that did not exist during the development phase of the software. We propose a me... Read More about Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language.

Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services (2023)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Eckerle, D., Farrenkopf, T., & Guckert, M. (2023, June). Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services. Presented at 37th ECMS International Conference on Modelling and Simulation, Florence, Italy

With the number of individual vehicles meeting the capacity limit of urban road infrastructure, the deployment of new mobility services may help to achieve more efficient use of available resources and prevent critical overload. It may be observed th... Read More about Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services.

Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics (2023)
Presentation / Conference Contribution
Urquhart, N., & Hart, E. (2023, April). Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics. Presented at Evo Applications 2023, Brno, Czech Republic

Quality-diversity (QD) methods such as MAP-Elites have been demonstrated to be useful in the domain of combinatorial optimisation due to their ability to generate a large set of solutions to a single-objective problem that are diverse with respect to... Read More about Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics.

Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations (2022)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2022, November). Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations. Presented at 24th International Conference on Principles and Practice of Multi-Agent Systems, Valencia, Spain

Cause-effect graphs have been applied in non agent-based simulations, where they are used to model chained causal relations between input parameters and system behaviour measured by appropriate indicators. This can be useful for the analysis and inte... Read More about Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations.

Using Semantic Technology to Model Persona for Adaptable Agents (2021)
Presentation / Conference Contribution
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021, June). Using Semantic Technology to Model Persona for Adaptable Agents. Presented at ECMS 2021

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. A... Read More about Using Semantic Technology to Model Persona for Adaptable Agents.

Modelling Individual Preferences to Study and Predict Effects of Traffic Policies (2021)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021, October). Modelling Individual Preferences to Study and Predict Effects of Traffic Policies. Presented at PAAMS: International Conference on Practical Applications of Agents and Multi-Agent Systems, Salamanca, Spain

Traffic can be viewed as a complex adaptive system in which systemic patterns arise as emergent phenomena. Global behaviour is a result of behavioural patterns of a large set of individual travellers. However, available traffic simulation models lack... Read More about Modelling Individual Preferences to Study and Predict Effects of Traffic Policies.

Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour (2021)
Presentation / Conference Contribution
Nguyen, J., Powers, S. T., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021, October). Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour. Presented at PAAMS: International Conference on Practical Applications of Agents and Multi-Agent Systems, Salamanca, Spain

AGADE Traffic is an agent-based traffic simulator that can be used to analyse purpose-driven travel behaviour of individuals that leads to the emergence of systemic patterns in mobility. The simulator uses semantic technology to model knowledge of in... Read More about Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour.

Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times (2021)
Presentation / Conference Contribution
Kittel, F., Enekel, J., Guckert, M., Holznigenkemper, J., & Urquhart, N. (2021, July). Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times. Presented at Genetic and Evolutionary Computation Conference (GECCO '21), Online

Parallel machine scheduling is a problem of high practical relevance for the manufacturing industry. In this paper, we address a variant in which an unweighted combination of earliness, tardiness and setup times aggregated in a single objective funct... Read More about Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times.

Real Time Optimisation of Traffic Signals to Prioritise Public Transport (2021)
Presentation / Conference Contribution
Plötz, P., Wittpohl, M., & Urquhart, N. (2021, April). Real Time Optimisation of Traffic Signals to Prioritise Public Transport. Presented at EvoApplications 2021, Online

This paper examines the optimisation of traffic signals to prioritise public transportation (busses) in real time. A novel representation for the traffic signal prioritisation problem is introduced. Through the novel representation a creative evoluti... Read More about Real Time Optimisation of Traffic Signals to Prioritise Public Transport.

Automated, Explainable Rule Extraction from MAP-Elites archives (2021)
Presentation / Conference Contribution
Urquhart, N., Höhl, S., & Hart, E. (2021, April). Automated, Explainable Rule Extraction from MAP-Elites archives. Presented at EvoAPPs2021, Online

Quality-diversity(QD) algorithms that return a large archive of elite solutions to a problem provide insights into how high-performing solutions are distributed throughout a feature-space defined by a user — they are often described as illuminating t... Read More about Automated, Explainable Rule Extraction from MAP-Elites archives.