All Outputs (79)

Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language (2024)
Conference Proceeding
Urquhart, N., & Hunter, K. (2024). Evolving Staff Training Schedules using an Extensible Fitness Function and a Domain Specific Language. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation (83–97). https://doi.org/10.1007/978-3-031-56852-7_6

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.

The stuff we swim in: Regulation alone will not lead to justifiable trust in AI (2023)
Journal Article
Powers, S. T., Linnyk, O., Guckert, M., Hannig, J., Pitt, J., Urquhart, N., …Weber, T. (2023). The stuff we swim in: Regulation alone will not lead to justifiable trust in AI. IEEE technology & society magazine, 42(4), 95-106. https://doi.org/10.1109/MTS.2023.3341463

Information technology is used ubiquitously and has become an integral part of everyday life. With the ever increasing pervasiveness and persuasiveness of Artificial Intelligence (AI), the function of socio-technical systems changes and must be consi... Read More about The stuff we swim in: Regulation alone will not lead to justifiable trust in AI.

Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services (2023)
Conference Proceeding
Nguyen, J., Powers, S., Urquhart, N., Eckerle, D., Farrenkopf, T., & Guckert, M. (2023). Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services. In ECMS2023 Proceedings

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)
Conference Proceeding
Urquhart, N., & Hart, E. (2023). Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics. In Applications of Evolutionary Computation – 26th International Conference, EvoApplications 2023 (35-52). https://doi.org/10.1007/978-3-031-30229-9

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.

Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World (2022)
Book
Urquhart, N. (2022). Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World. Cham: Springer. https://doi.org/10.1007/978-3-030-98108-2

This book explains classic routing and transportation problems and solutions, before offering insights based on successful real-world solutions. The chapters in Part I introduce and explain the traveling salesperson problem (TSP), vehicle routing pro... Read More about Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World.

Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations (2022)
Conference Proceeding
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2022). Multi-Agent Modelling Notation (MAMN): A multi-layered graphical modelling notation for agent-based simulations. In PRIMA 2022: Principles and Practice of Multi-Agent Systems - 24th International Conference, Valencia, Spain, November 16–18, 2022, Proceedings (640-649). https://doi.org/10.1007/978-3-031-21203-1_42

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.

An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos (2022)
Journal Article
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2022). An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos. Empirical Software Engineering, 27(7), Article 180. https://doi.org/10.1007/s10664-022-10210-w

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL model... Read More about An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos.

Modelling the Impact of Individual Preferences on Traffic Policies (2022)
Journal Article
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2022). Modelling the Impact of Individual Preferences on Traffic Policies. SN Computer Science, 3(5), Article 365. https://doi.org/10.1007/s42979-022-01253-3

Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individ... Read More about Modelling the Impact of Individual Preferences on Traffic Policies.

Using Semantic Technology to Model Persona for Adaptable Agents (2021)
Conference Proceeding
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021). Using Semantic Technology to Model Persona for Adaptable Agents. In ECMS 2021, 35th Proceedings (172-178). https://doi.org/10.7148/2021

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.

An overview of agent-based traffic simulators (2021)
Journal Article
Nguyen, J., Powers, S. T., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021). An overview of agent-based traffic simulators. Transportation Research Interdisciplinary Perspectives, 12, Article 100486. https://doi.org/10.1016/j.trip.2021.100486

Individual traffic significantly contributes to climate change and environmental degradation. Therefore, innovation in sustainable mobility is gaining importance as it helps to reduce environmental pollution. However, effects of new ideas in mobility... Read More about An overview of agent-based traffic simulators.

Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour (2021)
Conference Proceeding
Nguyen, J., Powers, S. T., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021). Using AGADE Traffic to Analyse Purpose-driven Travel Behaviour. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good: The PAAMS Collection 19th International Conference, PAAMS 2021, Salamanca, Spain, October 6–8, 2021, Proceedings (363-366). https://doi.org/10.1007/978-3-030-85739-4_33

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.

Modelling Individual Preferences to Study and Predict Effects of Traffic Policies (2021)
Conference Proceeding
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2021). Modelling Individual Preferences to Study and Predict Effects of Traffic Policies. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection 19th International Conference, PAAMS 2021, Salamanca, Spain, October 6–8, 2021, Proceedings (163-175). https://doi.org/10.1007/978-3-030-85739-4_14

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.

Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times (2021)
Conference Proceeding
Kittel, F., Enekel, J., Guckert, M., Holznigenkemper, J., & Urquhart, N. (2021). Optimisation Algorithms for Parallel Machine Scheduling Problems with Setup Times. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (131-132). https://doi.org/10.1145/3449726.3459487

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.

A Conceptual Framework for Establishing Trust in Real World Intelligent Systems (2021)
Journal Article
Guckert, M., Gumpfer, N., Hannig, J., Keller, T., & Urquhart, N. (2021). A Conceptual Framework for Establishing Trust in Real World Intelligent Systems. Cognitive Systems Research, 68, 143-155. https://doi.org/10.1016/j.cogsys.2021.04.001

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending either on s... Read More about A Conceptual Framework for Establishing Trust in Real World Intelligent Systems.

Real Time Optimisation of Traffic Signals to Prioritise Public Transport (2021)
Conference Proceeding
Plötz, P., Wittpohl, M., & Urquhart, N. (2021). Real Time Optimisation of Traffic Signals to Prioritise Public Transport. In Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021 (162-177). https://doi.org/10.1007/978-3-030-72699-7_11

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)
Conference Proceeding
Urquhart, N., Höhl, S., & Hart, E. (2021). Automated, Explainable Rule Extraction from MAP-Elites archives. In Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021 (258-272). https://doi.org/10.1007/978-3-030-72699-7_17

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.

Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation (2020)
Conference Proceeding
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation.

Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging tr... Read More about Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation.

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.

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.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Conference Proceeding
Urquhart, N., Guckert, M., & Powers, S. (2019). Increasing Trust in Meta-Heuristics by Using MAP-Elites. In GECCO '19 Companion (1345-1348). https://doi.org/10.1145/3319619.3326816

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can not be fully retraced because the flow of control is dependent on stochas... Read More about Increasing Trust in Meta-Heuristics by Using MAP-Elites.