Discovery Early Career Researcher Award - Grant ID: DE240100042
Funder
Australian Research Council
Funding Amount
$339,237.00
Summary
Hybrid optimisation for coordinating autonomous trucks and drones. This project aims to build analytics for controlling a fleet of autonomous trucks and drones working in tandem to deliver retail goods and disaster relief. This project expects to develop new mathematical and artificial intelligence algorithms for routing and scheduling the vehicles and for directing the multi-modal transfer of goods between vehicles in real-time as traffic conditions change. Expected outcomes of this project inc ....Hybrid optimisation for coordinating autonomous trucks and drones. This project aims to build analytics for controlling a fleet of autonomous trucks and drones working in tandem to deliver retail goods and disaster relief. This project expects to develop new mathematical and artificial intelligence algorithms for routing and scheduling the vehicles and for directing the multi-modal transfer of goods between vehicles in real-time as traffic conditions change. Expected outcomes of this project include new theories and technologies that enable a central computer to remotely control the autonomous fleet for maximum efficiency. Benefits in transport and logistics include improved freight productivity through reducing costs and delivery times.Read moreRead less
Robust Reformulation Methods. Many decision problems in engineering, business and economics are modeled as nonlinear continuous optimization problems. Often these are made difficult by the existence of constraints. In this project, we reformulate such problems as constrained nonsmooth equations, rather than optimization problems, and develop generalized Newton and quasi-Newton methods for solving them. The expected outcomes of this project include a systematic theory of reformulation methods, ....Robust Reformulation Methods. Many decision problems in engineering, business and economics are modeled as nonlinear continuous optimization problems. Often these are made difficult by the existence of constraints. In this project, we reformulate such problems as constrained nonsmooth equations, rather than optimization problems, and develop generalized Newton and quasi-Newton methods for solving them. The expected outcomes of this project include a systematic theory of reformulation methods, and robust and efficient algorithms for solving some important nonlinear continuous optimization problems. There is high potential for applications in engineering, business and finance.Read moreRead less
Quadratic Support Function Technique to Solving Hard Global Nonconvex Optimization Problems. Optimization techniques are becoming increasingly beneficial to modern Australian society in areas such as manufacturing and commerce by improving technical and management decisions. The proposed research is expected to produce enhanced optimization techniques that can be applied to solve a wider range of important problems too complex to be currently solved. The proposed research also represents an inte ....Quadratic Support Function Technique to Solving Hard Global Nonconvex Optimization Problems. Optimization techniques are becoming increasingly beneficial to modern Australian society in areas such as manufacturing and commerce by improving technical and management decisions. The proposed research is expected to produce enhanced optimization techniques that can be applied to solve a wider range of important problems too complex to be currently solved. The proposed research also represents an international collaboration which will improve Australia's ability to participate effectively in international research and innovation and to produce globally competitive mathematical technologiesRead moreRead less
Continuous Optimization with Linear Matrix Inequality Constraints. The proposed research is expected to lead to new insights and new joint collaborative work for both Autralian and Korean partners. Joining forces of the two teams will ensure that a full range of techniques can be utilized to provide rapid successful research outcomes. The proposed collaboration will give better opportunity to increase the visibility of the work from Korea in Australia, and vice versa. One of the key national be ....Continuous Optimization with Linear Matrix Inequality Constraints. The proposed research is expected to lead to new insights and new joint collaborative work for both Autralian and Korean partners. Joining forces of the two teams will ensure that a full range of techniques can be utilized to provide rapid successful research outcomes. The proposed collaboration will give better opportunity to increase the visibility of the work from Korea in Australia, and vice versa. One of the key national benefits is that the proposed research collaboration will provide extremly fertile ground for training postdoctoral researchers and graduate students in one of the most applicable areas of mathematics.Read moreRead less
Necessary and sufficient conditions for global minimum in multi-extremal global continuous optimization. A basic understanding of the mechanisms for finding local "best" (optimal) solutions has been
achieved through optimization techniques. However, solving global optimization problems, where we may have many local optimal solutions which are not the "absolutely best" (global), is vital for many applications in industry & science, and is intrinsically difficult. The lack of verifiable condition ....Necessary and sufficient conditions for global minimum in multi-extremal global continuous optimization. A basic understanding of the mechanisms for finding local "best" (optimal) solutions has been
achieved through optimization techniques. However, solving global optimization problems, where we may have many local optimal solutions which are not the "absolutely best" (global), is vital for many applications in industry & science, and is intrinsically difficult. The lack of verifiable conditions for a global optimum is a serious limitation. This project will develop verifiable such global optimality conditions for many classes of these problems. A new methodology, functional abstract convexity, developed by CIs and has shown promising results, will be extended and applied for solving these problems.Read moreRead less
A new improved solution to global optimization over multivariate polynomials: Mathematical principles, numerical methods and selected applications. Optimization technology is becoming increasingly beneficial to modern Australian society in areas such as wireless communications and manufacturing by improving performance or reducing costs. Our research will produce enhanced global optimization methodologies, capable of solving a wider range of problems that are currently too complex to be solved. ....A new improved solution to global optimization over multivariate polynomials: Mathematical principles, numerical methods and selected applications. Optimization technology is becoming increasingly beneficial to modern Australian society in areas such as wireless communications and manufacturing by improving performance or reducing costs. Our research will produce enhanced global optimization methodologies, capable of solving a wider range of problems that are currently too complex to be solved. Since global optimization technology is used in many scientific disciplines and modern industrial applications, the research will make many Australian science and industries more competitive. Our research also represents a program of high profile international collaborations that will improve Australia's ability to produce internationally competitive optimization technology.
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
Optimizing Outpatient Parenteral Antibiotic Therapy To Support Hospital-in-the-home Program Across The Unique Environmental Conditions Of Australia
Funder
National Health and Medical Research Council
Funding Amount
$645,205.00
Summary
This project aims to solve problems associated with stability and dosing of antibiotic infusions given to patients in their homes, to support decision making by doctors and regulators. Currently, there is a lack of adequate data that complies with contemporary requirements. We will study infusion preparation both in laboratory settings and in ‘real-life’ conditions while being used by patients. We will enhance the stability of antibiotic preparations and optimize doses for effective treatment.
Derivative free algorithms for large scale nonsmooth and global optimization and their applications. The outcomes expected from this research fall broadly into two categories: 1) the development of a new class of effective readily implementable derivative free techniques for large scale non-smooth and global optimisation and 2) the development of new algorithms based on derivative free optimization techniques for solving data mining, resource allocation problems and some problems in bioinformati ....Derivative free algorithms for large scale nonsmooth and global optimization and their applications. The outcomes expected from this research fall broadly into two categories: 1) the development of a new class of effective readily implementable derivative free techniques for large scale non-smooth and global optimisation and 2) the development of new algorithms based on derivative free optimization techniques for solving data mining, resource allocation problems and some problems in bioinformatics. In particular, the application of these techniques to molecular biology and cluster analysis will be very important for the development of competitive technologies for Australia.
Read moreRead less