Real-time scheduling of trains to control peak electricity demand. This project aims to develop new scheduling and control methods that will enable railways to reduce their demand for electricity during peak demand periods, without undue disruption to the timetable.
These new methods and systems will integrate with—and expand the capabilities of—an Australian train control system that is used by railways around the world. This will enable better management of electricity within a region and be ....Real-time scheduling of trains to control peak electricity demand. This project aims to develop new scheduling and control methods that will enable railways to reduce their demand for electricity during peak demand periods, without undue disruption to the timetable.
These new methods and systems will integrate with—and expand the capabilities of—an Australian train control system that is used by railways around the world. This will enable better management of electricity within a region and better use of renewable energy sources, with significant cost savings for railways and the wider community.Read moreRead less
Mathematical Decision Support to Optimise Hospital Capacity and Utilisation. Hospital planners and executives regularly contend with challenging capacity related decisions. Decisions relating to prioritisation, allocation and sharing of resources have a profound impact on productivity, efficiency and patient outcomes. There is a lack of data-driven or quantitative decision support to make well-informed capacity related decisions of a strategic or tactical nature in a single hospital, or across a ....Mathematical Decision Support to Optimise Hospital Capacity and Utilisation. Hospital planners and executives regularly contend with challenging capacity related decisions. Decisions relating to prioritisation, allocation and sharing of resources have a profound impact on productivity, efficiency and patient outcomes. There is a lack of data-driven or quantitative decision support to make well-informed capacity related decisions of a strategic or tactical nature in a single hospital, or across a regional healthcare system. This project aims to deliver decision support for holistic hospital capacity assessment and planning optimisation. This will yield significant benefits for the health sector, providing a tool to optimise the allocation of resources and provision of infrastructure for regional hospital services.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
Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiator ....Determining features that separate groups of protein sequences. This project aims to develop mathematical approaches for determining features that distinguish one group of proteins from another, based on their amino acid sequences. The groups of sequences will reflect different outcomes, so that identifying the fundamental features can result in targeted interventions against the poorer outcome. A simple comparison at each position or of known features can fail to determine robust differentiators and so more complex methods are required. The project will, for example, help identify HIV vaccine targets by comparing early HIV transmission sequences from those in chronic infection. The methods will be applicable to viral proteins where high mutation rates make this task even more complex.Read moreRead less
A unified approach to the design of minimum length networks. This project aims to develop a new approach to designing minimum length interconnection networks by analysing their geometric structure. These networks form the basis of communication, power and transport systems. Optimising the design of such networks is a mathematically challenging problem of high computational complexity. This project will use an innovative method based on a relationship between the geometry of networks and a type o ....A unified approach to the design of minimum length networks. This project aims to develop a new approach to designing minimum length interconnection networks by analysing their geometric structure. These networks form the basis of communication, power and transport systems. Optimising the design of such networks is a mathematically challenging problem of high computational complexity. This project will use an innovative method based on a relationship between the geometry of networks and a type of partitioning of the plane called an oriented Voronoi diagram. The outcome will be efficient new algorithms for designing physical networks, which, in practice, will ultimately lead to a reduction in network infrastructure costs for industries in Australia.
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Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. Thi ....Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. This is expected to support the manufacturing, retail, delivery and mobile fleets industries.Read moreRead less
Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less
Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and ....Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and accelerating growth, imply that application of methods developed through this project may save billions of dollars and, more importantly, thousands of lives. An expected outcome of this project will be superior theoretical and practical methods for analysing productivity and efficiency of economic systems, to enhance understanding of the potential for improvements and of the necessary reforms.Read moreRead less
Large scale nonsmooth, nonconvex optimisation. This project aims to develop, analyse, test and apply (sub) gradient-based methods for solving large scale nonsmooth, nonconvex optimisation problems. Large scale problems with complex nonconvex objective and/or constraint functions are among the most difficult in optimisation. This project will generate new knowledge in numerical optimisation and machine learning. The use of structures and sparsity of large scale problems will lead to the developme ....Large scale nonsmooth, nonconvex optimisation. This project aims to develop, analyse, test and apply (sub) gradient-based methods for solving large scale nonsmooth, nonconvex optimisation problems. Large scale problems with complex nonconvex objective and/or constraint functions are among the most difficult in optimisation. This project will generate new knowledge in numerical optimisation and machine learning. The use of structures and sparsity of large scale problems will lead to the development of better models, and more accurate and robust methods. The expected outcomes of the project are ready-to-implement and apply numerical methods for solving large-scale, nonsmooth, nonconvex optimisation problems, as well as problems in machine learning and regression analysis.Read moreRead less
Incentivised strategic traffic assignment: bi-level transport optimisation. This project aims to advance the fundamental knowledge base and methodological modelling capacity related to traffic network assignment representing complex incentive structures such as network pricing, behavioural shift inducement, dynamic speed control and information-provision. Expected outcomes include new equilibrium formulations characterising traveller responses to, and interactions with, incentive structures whil ....Incentivised strategic traffic assignment: bi-level transport optimisation. This project aims to advance the fundamental knowledge base and methodological modelling capacity related to traffic network assignment representing complex incentive structures such as network pricing, behavioural shift inducement, dynamic speed control and information-provision. Expected outcomes include new equilibrium formulations characterising traveller responses to, and interactions with, incentive structures while maintaining complex stochastic adaptive behaviours from previous research, new network routing algorithms, and a novel bi-level optimisation approach for seeking optimal incentive policies. The project will provide a scientific basis for the quantified network evaluation of incentivisation strategies that will support enhanced transport planning thereby improving mobility across society.Read moreRead less