Faster, cheaper, better: mathematical advances for improved design and scheduling of robotic instrumentation. This project extends previous research addressing mathematical challenges in the optimal design and scheduling of robotic instrumentation. The Partner Organisation manufactures instruments for cancer diagnostics, and designs instruments that need to produce rapid, high-quality results, at a reasonable cost in a competitive market. It is intended that powerful new scheduling algorithms wi ....Faster, cheaper, better: mathematical advances for improved design and scheduling of robotic instrumentation. This project extends previous research addressing mathematical challenges in the optimal design and scheduling of robotic instrumentation. The Partner Organisation manufactures instruments for cancer diagnostics, and designs instruments that need to produce rapid, high-quality results, at a reasonable cost in a competitive market. It is intended that powerful new scheduling algorithms will be devised to handle their complex problem, which is more challenging than standard problems. The developed methodologies aim to reduce the product development cycle and boost the competitiveness of Australian manufacturers. In addition, new theoretical and algorithmic contributions aim to enable improved scheduling in other application areas.Read moreRead less
New Theory and Algorithms for Nonsmooth Optimisation with Application to Integer Programming. Mathematical optimisation plays a key role in a wide variety of applications in business, industry, engineering and science. For example, airlines cannot fly and radiation treatment for cancer cannot be delivered without solving (a series of) optimisation problems. Some classes of optimisation problem are very well solved, with clear mathematical foundations, efficient algorithms, and reliable software ....New Theory and Algorithms for Nonsmooth Optimisation with Application to Integer Programming. Mathematical optimisation plays a key role in a wide variety of applications in business, industry, engineering and science. For example, airlines cannot fly and radiation treatment for cancer cannot be delivered without solving (a series of) optimisation problems. Some classes of optimisation problem are very well solved, with clear mathematical foundations, efficient algorithms, and reliable software implementations. Both nonsmooth and integer optimisation problems have a good mathematical basis, but there are "gaps"; existing methods cannot always solve real industrial problems. This project will deliver better methods, built on better theory, and so will yield better solutions for important applications.Read moreRead less
Modelling the structure of Australian wool auction prices. Australian wool auction ($3.5-4 billions per year) is an on-going process. The prices paid in this auction market are used by the Australian production and service sectors to identify the quality preferences the international retail markets and the intermediate processors. The proposed research will optimise the information that can be extracted and used by these sectors in the production and distribution of the raw wool clip. A two- ....Modelling the structure of Australian wool auction prices. Australian wool auction ($3.5-4 billions per year) is an on-going process. The prices paid in this auction market are used by the Australian production and service sectors to identify the quality preferences the international retail markets and the intermediate processors. The proposed research will optimise the information that can be extracted and used by these sectors in the production and distribution of the raw wool clip. A two-stages algorithm in tree-based regression will be developed. The project will provide a challenge environment to train a Ph.D. student in agriculture modelling and optimisation.Read moreRead less
Doubly Stochastic Matrices & The Hamiltonian Cycle Problem. The classical hard problem of determining whether a given graph possesses a Hamiltonian cycle contains the essential difficulty of the famous 'Travelling Salesman Problem'. A characterisation of this difficulty in terms of variability of returns (to the initial state) in a controlled stochastic process will be a significant conceptual advance with repercussions in a number of fields including optimisation and theoretical computer scien ....Doubly Stochastic Matrices & The Hamiltonian Cycle Problem. The classical hard problem of determining whether a given graph possesses a Hamiltonian cycle contains the essential difficulty of the famous 'Travelling Salesman Problem'. A characterisation of this difficulty in terms of variability of returns (to the initial state) in a controlled stochastic process will be a significant conceptual advance with repercussions in a number of fields including optimisation and theoretical computer science. Algorithmic advances exploiting such a characterisation will significantly contribute to existing technologies for solving problems in applications ranging from logistics to cryptography. Since TSP describes certain efficient ways of routing its applicability to information networks is clear.Read moreRead less
An optimisation-based framework for non-classical Chebyshev approximation. This project aims to solve open mathematical problems in multivariate and piecewise polynomial approximations, two directions that correspond to fundamental obstacles to extending classical approximation results. Through an innovative combination of optimisation and algebraic technique, the project intends to develop foundations for new results in approximation theory, and new insights into other areas of mathematics, mos ....An optimisation-based framework for non-classical Chebyshev approximation. This project aims to solve open mathematical problems in multivariate and piecewise polynomial approximations, two directions that correspond to fundamental obstacles to extending classical approximation results. Through an innovative combination of optimisation and algebraic technique, the project intends to develop foundations for new results in approximation theory, and new insights into other areas of mathematics, most notably optimisation. The techniques and methods developed should also have significant benefits in the many disciplines where approximation problems appear, such as engineering, physics or data mining. The research outputs resulting from this project will be used in a wide range of fields to help implement programs, policies and improve decision making.Read moreRead less
Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to devel ....Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to develop purely data-driven rules to choose the regularisation parameter and show how they work in theory, and in practice. It will also develop convex framework, acceleration strategies as well as preconditioning and splitting ideas to design efficient regularisation solvers.Read moreRead less
Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation a ....Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation algorithms specially designed for distributed systems. The framework is expected to produce a suite of algorithms, each customised to exploit a specific network configuration. The project will provide significant benefits in distributed machine learning applications such as federated learning.Read moreRead less
ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this te ....ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this team with the foremost international authorities and leading industry players in the area of sensor networks. This research network will guide collaborative research that will ensure Australia to play a world leading role in sensor network development and implementation.
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Stationarity and regularity in variational analysis with applications to optimization. This project will significantly develop the theoretical basis of variational analysis and optimization. Improving the understanding of regularity and stationarity issues in optimization theory will lead to major national benefits in increasing efficiencies and reducing costs in many fields of human endeavour on a national and international level.
Improving train flows with connected driver advice systems. The project aims to develop new train control theory to determine the efficient movement of multiple trains, and to demonstrate a practical system for coordinating trains, on busy intercity rail corridors. Railways around the world are now deploying driver advice systems developed by the research team and the partner organisation, TTG Transportation Technology. The project is designed to enable these systems to coordinate the movements ....Improving train flows with connected driver advice systems. The project aims to develop new train control theory to determine the efficient movement of multiple trains, and to demonstrate a practical system for coordinating trains, on busy intercity rail corridors. Railways around the world are now deploying driver advice systems developed by the research team and the partner organisation, TTG Transportation Technology. The project is designed to enable these systems to coordinate the movements of many trains on a congested rail network to improve timekeeping, smooth the flow of traffic, increase capacity and reduce energy use.Read moreRead less