A modelling framework for designing more sustainable urban freight systems. How to improve the sustainability of goods movement in cities is a major challenge for society. City logistics involves numerous stakeholders, including carriers that are small and independent and have difficulty achieving high levels of efficiency. This project aims to develop an integrated modelling framework to facilitate the exploration of novel urban logistics initiatives that are more connected, collaborative, and ....A modelling framework for designing more sustainable urban freight systems. How to improve the sustainability of goods movement in cities is a major challenge for society. City logistics involves numerous stakeholders, including carriers that are small and independent and have difficulty achieving high levels of efficiency. This project aims to develop an integrated modelling framework to facilitate the exploration of novel urban logistics initiatives that are more connected, collaborative, and open. The framework combines agent-based simulation, optimization, artificial intelligence and digital twin technologies to design and evaluate new schemes for improving the efficiency, reliability, and sustainability of urban logistics systems, which will alleviate congestion and the need for new road infrastructure.Read moreRead less
Integrating land use, market equilibrium, and transport for city planning. This project is significant because it offers a comprehensive travel demand modelling platform that provides realistic, robust, and self-consistent metrics for transport infrastructure planning addressing contemporary changes in the transport system. The expected outcomes of the platform are incorporating recent advances in activity-based methods for travel demand modelling, developing a dynamic and integrated system for ....Integrating land use, market equilibrium, and transport for city planning. This project is significant because it offers a comprehensive travel demand modelling platform that provides realistic, robust, and self-consistent metrics for transport infrastructure planning addressing contemporary changes in the transport system. The expected outcomes of the platform are incorporating recent advances in activity-based methods for travel demand modelling, developing a dynamic and integrated system for modelling short- and long-term household decisions, and creating a systematic calibration mechanism to handle the large-scale model. The benefits of this platform to the Australian transport industry and authorities will be demonstrated in use cases to design and optimise pricing for a multiplayer transport network.Read moreRead less
Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analyti ....Time consistency, risk-mitigation and partially observable systems. This project aims to find optimal decision rules that mitigate risk in a time consistent manner for partially observable systems. Many problems in conservation management and engineering systems are dependent on random environments and entail risk of failure. The challenge of consistently minimising such a risk while achieving satisfactory and sustainable resource consumption is considerable. This project aims to develop analytical and numerical methods for optimal control in such scenarios. These methods will have application to fishery management, communication networks, power systems and social resource allocation scenarios.Read moreRead less
Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project ....Large Markov decision processes and combinatorial optimisation. Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project aims to provide theoretically sound frameworks for solving large Markov decision processes, and exploit them to solve important combinatorial optimisation problems. This timely project can promote Australia's position in the development of such novel frameworks for many scientific and industrial applications.Read moreRead less
An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through th ....An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of pioneering natural language processing components and novel custom-made machine-readable knowledge bases. The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.Read moreRead less
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.Read moreRead less
Safe and efficient eco-driving using connected and automated vehicles. This project aims to solve the paradox of trading off liveability for mobility by simultaneously reducing traffic congestion, vehicle energy consumption, and emission. This project is expected to generate fundamental knowledge and powerful tools on utilising connected and automated vehicles to help individuals become green drivers. Expected outcomes include ground-breaking models capable of holistically optimising traffic ef ....Safe and efficient eco-driving using connected and automated vehicles. This project aims to solve the paradox of trading off liveability for mobility by simultaneously reducing traffic congestion, vehicle energy consumption, and emission. This project is expected to generate fundamental knowledge and powerful tools on utilising connected and automated vehicles to help individuals become green drivers. Expected outcomes include ground-breaking models capable of holistically optimising traffic efficiency, energy consumption and emission, and innovative control strategies and policies that focus on energy efficiency and environment protection. This research will bring a wide range of substantial national benefits related to mobility, public health, environmental protection, and energy security.Read moreRead less