Generalizing Multi-level Decision Support Handling Multi-objectives, Multi-followers and Uncertainty for Critical Resource Planning. The proposed multi-level optimisation techniques and fuzzy multi-objective multi-follower multi-level decision support system can be used widely in government and industries of Australia to reduce decision blindness, improve decision effectiveness, and therefore has the potential to increase the competitiveness of organizations. Many organizations in Australia are ....Generalizing Multi-level Decision Support Handling Multi-objectives, Multi-followers and Uncertainty for Critical Resource Planning. The proposed multi-level optimisation techniques and fuzzy multi-objective multi-follower multi-level decision support system can be used widely in government and industries of Australia to reduce decision blindness, improve decision effectiveness, and therefore has the potential to increase the competitiveness of organizations. Many organizations in Australia are decentralized and have a hierarchical structure. The proposed techniques are extremely effective for such kinds of organizations in critical planning, management and policy making, including tourism resource planning, water resource management, financial planning, healthcare planning, land-use planning, production planning, transportation planning, and power market planning.Read moreRead less
Group Decision Support Systems for Fuzzy Multi-objective Decision Problems. Most real-world decisions in organisations are made by groups addressing multi-objectives. Further, the decision objectives are frequently characterized by fuzzy parameters and decision makers often utilise fuzzy judgments in attempting to reach optimal solutions. The project is the first to address all these issues: fuzzy objectives, fuzzy judgements, multi-objectives and groups in decision-making. The project will deve ....Group Decision Support Systems for Fuzzy Multi-objective Decision Problems. Most real-world decisions in organisations are made by groups addressing multi-objectives. Further, the decision objectives are frequently characterized by fuzzy parameters and decision makers often utilise fuzzy judgments in attempting to reach optimal solutions. The project is the first to address all these issues: fuzzy objectives, fuzzy judgements, multi-objectives and groups in decision-making. The project will develop a set of interactive decision-making methods to be used by groups solving fuzzy multi-objective decision problems with the allowance of fuzzy judgements, then develop a group decision support system to implement the methods. These outcomes can be immediately used by suitable Australian organisations.Read moreRead less
Ring constructions and algorithms for enhancing performance of BCH codes. BCH codes form a major class of codes used in modern communication systems. The aim of this project is to enhance the efficiency of this class of codes by combining them in constructions enabling correction of deletion and insertion errors, and develop efficient implementations of encoding and decoding algorithms incorporating soft decision methods for enhanced error correction. Significance of the project is explained by ....Ring constructions and algorithms for enhancing performance of BCH codes. BCH codes form a major class of codes used in modern communication systems. The aim of this project is to enhance the efficiency of this class of codes by combining them in constructions enabling correction of deletion and insertion errors, and develop efficient implementations of encoding and decoding algorithms incorporating soft decision methods for enhanced error correction. Significance of the project is explained by the role of fast, secure and reliable communications in modern information and communication technology. Expected outcomes include new efficient algorithms and commercial modules available for symbolic computation systems with applications in telecommunications industry.
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New Analytical Perspectives on the Algorithmic Complexity of the Hamiltonian Cycle Problem. Hamiltonian Cycle Problem (HCP), known - in the complexity theory of
algorithms -to be NP-hard is proposed for study, from three innovative,
separate (yet related) analytical perspectives: singularly perturbed
(controlled) Markov chains, that links the HCP with systems and control
theories; parametric nonconvex optimization, that links HCP with fast
interior point methods of modern optimization an ....New Analytical Perspectives on the Algorithmic Complexity of the Hamiltonian Cycle Problem. Hamiltonian Cycle Problem (HCP), known - in the complexity theory of
algorithms -to be NP-hard is proposed for study, from three innovative,
separate (yet related) analytical perspectives: singularly perturbed
(controlled) Markov chains, that links the HCP with systems and control
theories; parametric nonconvex optimization, that links HCP with fast
interior point methods of modern optimization and the spectral approach
based on a novel adaptation of Ihara-Selberg trace formula for regular
graphs. Our mathematical approach to this archetypal complex problem of graph
theory and discrete optimization promises to enhance the fundamental
understanding - and ultimate "managibility" - of the underlying
difficulty of HCP.
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Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a ....Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.Read moreRead less