ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less
Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, i ....Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, integer models usually assume the data is known with certainty, which is often not the case in the real world. This project will develop new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms. Read moreRead less
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
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
Evaluating the long-term costs and benefits of community-based initiatives. The ultimate benefit from the research is a more efficient allocation of public funds to provide public services, i.e. an increase in the gain derived from the government budget. The relative advantages of alternative methods of delivering government services are subject to significant uncertainty, which means that policy decisions are often poorly informed. Improvements in the accuracy of predicting the costs and benefi ....Evaluating the long-term costs and benefits of community-based initiatives. The ultimate benefit from the research is a more efficient allocation of public funds to provide public services, i.e. an increase in the gain derived from the government budget. The relative advantages of alternative methods of delivering government services are subject to significant uncertainty, which means that policy decisions are often poorly informed. Improvements in the accuracy of predicting the costs and benefits of complex community-based initiatives will help policymakers identify the set of initiatives that provide the best outcomes for the community they serve, as well as informing the optimal specification of the individual initiatives.Read moreRead less