Synchromodal container logistics for Australia. Synchromodal container logistics for Australia. This project aims to develop advanced mathematical optimization models and algorithms to create multi-modal logistics approaches for container movements in and out of Australia’s busy ports. The increasingly congested capital cities of Sydney, Brisbane and Melbourne need to find new ways of moving an increasing volume of containerized freight. Moving from trucks to rail is expected to reduce pollution ....Synchromodal container logistics for Australia. Synchromodal container logistics for Australia. This project aims to develop advanced mathematical optimization models and algorithms to create multi-modal logistics approaches for container movements in and out of Australia’s busy ports. The increasingly congested capital cities of Sydney, Brisbane and Melbourne need to find new ways of moving an increasing volume of containerized freight. Moving from trucks to rail is expected to reduce pollution and road congestion, but is only possible if highly efficient modes of operation can be developed. Research into system design and operational scheduling is expected to achieve the required efficiency for multi-modal logistics that will reduce air pollution and road congestion.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
Ensuring Australia's competitiveness by implementing targeted performance measurement systems across the extended supply chain. This project will develop a framework to guide managers in designing, implementing, and using performance measurement systems across the industry supply chain to maximise the potential benefits of supply chain management. The outcomes enhance organisational competitiveness, supply chain competitiveness and boost Australia's economy.
A real-time traffic signal system for safe and efficient intersections . Road traffic crashes result in 1,200 fatalities and another 36,500 injuries on Australian roads each year. Signalised intersections represent a high-risk node in a transportation network, but the current signal designs only consider efficiency but not safety. This project aims to unleash the power of artificial intelligence (AI) and integrate with the advanced extreme value models for proactive and efficient detection of cr ....A real-time traffic signal system for safe and efficient intersections . Road traffic crashes result in 1,200 fatalities and another 36,500 injuries on Australian roads each year. Signalised intersections represent a high-risk node in a transportation network, but the current signal designs only consider efficiency but not safety. This project aims to unleash the power of artificial intelligence (AI) and integrate with the advanced extreme value models for proactive and efficient detection of crash risk in real-time. Its innovations lie on developing a novel traffic signal control system balancing safety and efficiency of signalised intersections. The proposed real-time traffic signal system will fundamentally transform the intersection operation and lead to reductions of road fatalities, injuries and emissions.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
Discovery Early Career Researcher Award - Grant ID: DE130100291
Funder
Australian Research Council
Funding Amount
$374,595.00
Summary
Adaptive control of stochastic queueing networks. Queues of items competing for service appear on the road, in health-care, in manufacturing and in communication systems. This project will set up methodology for adaptive control and resource allocation for stochastic queueing network models applicable to a variety of scenarios accounting for parameter uncertainty.
Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-po ....Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-powered logistics vehicles are a major contributor. However, converting these trucks to LNG requires strong evidence to convince logistics companies of the benefits of shifting to green logistics. An increase in logistics productivity is expected to increase Australia’s gross domestic product by $2 billion, while this research should also provide vital data on sustainability issues and LNG conversions.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
Industrial Transformation Training Centres - Grant ID: IC190100026
Funder
Australian Research Council
Funding Amount
$4,969,663.00
Summary
ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway an ....ARC Training Centre for Cell and Tissue Engineering Technologies. The ARC Training Centre for Cell and Tissue Engineering Technologies aims to provide training to create a highly skilled workforce for the tissue engineering and regenerative medicine sector and to enhance research performance and innovation in Australia through fundamental and applied research carried out in industry-led PhD projects. The research aims to address major aspects of the manufacturing and commercialisation pathway and barriers faced by the sector, namely improving process efficiencies, enabling early-stage scale-up (cell/tissue) and development of the sector's supply chain. The knowledge created and research undertaken would help to accelerate commercialisation in regenerative medicine, tissue engineering and cell therapies.Read moreRead less