Development of methods and algorithms to support multidisciplinary optimisation. This project will aim to develop a number of novel and computationally efficient schemes to deal with the key challenges facing multidisciplinary optimisation. These advancements will allow us to solve a number of challenging and intractable problems in science and engineering.
Discovery Early Career Researcher Award - Grant ID: DE240100006
Funder
Australian Research Council
Funding Amount
$444,847.00
Summary
Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techn ....Robust Derivative-Free Algorithms for Complex Optimisation Problems. Mathematical optimisation gives a systematic way for optimal decision-making. This project aims to develop new mathematical tools for complex optimisation problems where limited problem information is available. It will generate new foundational theories for alternative optimisation tools, introducing substantial new capability and rigour to the discipline. The project will create significant new mathematical optimisation techniques and create world-leading and publicly available software. These new techniques and software may ultimately be able to solve some of the most complex optimisation problems in research and industry, such as improving long-term climate predictions and designing 3D-printed medical implants.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
Pervasive Grids with Autonomic Capabilities. A grid computing system that brings together a multitude of heterogonous resources able should be able to function continuously without much intervention by a human operator. This work aims at developing techniques and tools for the monitoring and prediction of the behaviour of the core structure of a grid. In this case, the ?core? structure is a large- or a wide-area network, or a collection of such networks. The monitoring process will feed into the ....Pervasive Grids with Autonomic Capabilities. A grid computing system that brings together a multitude of heterogonous resources able should be able to function continuously without much intervention by a human operator. This work aims at developing techniques and tools for the monitoring and prediction of the behaviour of the core structure of a grid. In this case, the ?core? structure is a large- or a wide-area network, or a collection of such networks. The monitoring process will feed into the other layers in the grid fabric important information (traffic, current and possible future congestions, failures, topological variations, etc) to enable the efficient and consistent operation of the grid. This is an important research problem in grid computing
since traditional assumptions that are more or less valid in conventional high-performance computing settings break down on the Grid.Read moreRead less
A Grid-Enabled Meta-Server for Protein Threading. Grid Computing is a driver for many e-Science research projects around the world today. The project investigates the use of grid technology in building a meta-server architecture for protein threading. Protein technology problems are important for the field of bioinformatics and they also influence many industries, such as, agriculture, drug design, food science, and many more. The proposed framework can be extended to other problems in the life ....A Grid-Enabled Meta-Server for Protein Threading. Grid Computing is a driver for many e-Science research projects around the world today. The project investigates the use of grid technology in building a meta-server architecture for protein threading. Protein technology problems are important for the field of bioinformatics and they also influence many industries, such as, agriculture, drug design, food science, and many more. The proposed framework can be extended to other problems in the life sciences such as bio- and health-informatics. Projects of this nature are significant and will enable Australia to maintain its pioneering position and international reputation among other nations as leaders in Information Technology.Read moreRead less
Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can g ....Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can greatly speed up an algorithm and improve its accuracy. This project aims to design improved algorithms that harness auxiliary data to solve selected high-impact NP-hard graph problems, and will build a new empowering theory to discern when auxiliary data can be used to improve algorithms.Read moreRead less
Holistic Energy-Aware Scheduling for Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Concerns of power (or energy) consumption have become increasingly significant in the context of the design as well as the use of distributed computing systems. Therefore, there is ....Holistic Energy-Aware Scheduling for Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Concerns of power (or energy) consumption have become increasingly significant in the context of the design as well as the use of distributed computing systems. Therefore, there is a need to develop new generation of algorithms and software tools that enable the creation of environmentally friendly 'green' distributed systems. This project is a major step in this direction.Read moreRead less
Data and Job Scheduling in Large-Scale Distributed Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc.). Thus, a distributed system can be viewed as a collection of computing and communication resources shared by active users. Towards this end, a new generation of algorithms and software tool ....Data and Job Scheduling in Large-Scale Distributed Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc.). Thus, a distributed system can be viewed as a collection of computing and communication resources shared by active users. Towards this end, a new generation of algorithms and software tools need to be developed for the efficient utilisation of these systems through an appropriate allocation of the available resources to competing applications and users. This project is a major step in this direction.Read moreRead less
Replica Placement in Data-Intensive Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Thus, a distributed system can be viewed as a collection of computing, storage and communication resources shared by active users. Towards this end, a new generation of algorithms an ....Replica Placement in Data-Intensive Distributed Computing Systems. Distributed computing systems are the platform of choice for many applications. In these systems, applications are submitted by a large number of users that compete for the shared heterogeneous resources (computers, storage communication links, etc). Thus, a distributed system can be viewed as a collection of computing, storage and communication resources shared by active users. Towards this end, a new generation of algorithms and software tools need to be developed for the efficient utilisation of these systems through an appropriate allocation of data to competing applications and users. This project is a major step in this direction.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101761
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Solving intractable problems: from practice to theory and back. By analysing how theoretically intractable problems are solved in practice by highly optimised software solvers, this project aims at a better theoretical understanding of these problems. The gained mathematical insights will then be used to stimulate the development of new and improved software solvers.