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All Outputs (75)

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)
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.

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)
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.

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.

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.

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)
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.

Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation (2020)
Presentation / Conference Contribution
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020, February). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation. Presented at Modelling 2020, Vienna

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.

Increasing Trust in Meta-Heuristics by Using MAP-Elites (2019)
Presentation / Conference Contribution
Urquhart, N., Guckert, M., & Powers, S. (2019, July). Increasing Trust in Meta-Heuristics by Using MAP-Elites. Presented at Genetic and Evolutionary Computation COnference, Prague, Czech Republic

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.

An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem (2019)
Presentation / Conference Contribution
Urquhart, N., Hoehl, S., & Hart, E. (2019, July). An Illumination Algorithm Approach to Solving the Micro-Depot Routing Problem. Presented at Genetic and Evolutionary Computation Conference (GECCO '19), Prague, Czech Republic

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.

Simulating Dynamic Vehicle Routing Problems with Athos (2019)
Presentation / Conference Contribution
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019, June). Simulating Dynamic Vehicle Routing Problems with Athos. Presented at ECMS2019: 33rd INTERNATIONAL ECMS CONFERENCE ON MODELLING AND SIMULATION, Napoli, Italy

Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human expert and at the same time processible by a computer system that is supposed... Read More about Simulating Dynamic Vehicle Routing Problems with Athos.

An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems (2019)
Presentation / Conference Contribution
Urquhart, N., & Powers, S. T. (2019, June). An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems. Presented at PAAMS 2019: International Conference on Practical Applications of Agents and Multi-Agent Systems, Avila, Spain

We present an agent based framework for improving multi-stakeholder optimisation problems, which we define as optimisation problems where the solution is utilised by a number of stakeholders who have their own local preferences. We explore our ideas... Read More about An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems.

Simulating the actions of commuters using a multi-agent system (2019)
Journal Article
Urquhart, N., Powers, S., Wall, Z., Fonzone, A., Ge, J., & Polhill, G. (2019). Simulating the actions of commuters using a multi-agent system. Journal of Artificial Societies and Social Simulation, 22(2), https://doi.org/10.18564/jasss.4007

The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is desirable to have a means of simulating commuting in order to allow organisat... Read More about Simulating the actions of commuters using a multi-agent system.

Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. (2019)
Presentation / Conference Contribution
Urquhart, N., Hart, E., & Hutcheson, W. (2019, April). Quantifying the effects of increasing user choice in MAP-Elites applied to a Workforce Scheduling and Routing Problem. Presented at EvoStar2019: International Conference on the Applications of Evolutionary Computation, Leipzig

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..