Aggregating Generalised Stochastic Petri Nets for improved Performance Analysis. Australia's economy is very dependent on the operation of complex man-made systems. Important examples are telecommunication networks and services (e.g. the Internet), manufacturing plants, organisational processes, military logistics and transport systems (e.g. air traffic control). The performance of these systems is critical to their success. Thus being able to predict performance before systems are implemented i ....Aggregating Generalised Stochastic Petri Nets for improved Performance Analysis. Australia's economy is very dependent on the operation of complex man-made systems. Important examples are telecommunication networks and services (e.g. the Internet), manufacturing plants, organisational processes, military logistics and transport systems (e.g. air traffic control). The performance of these systems is critical to their success. Thus being able to predict performance before systems are implemented is very important in their design. This project will develop leading-edge performance analysis techniques and tools for an important class of practical systems. There is potential to commercialise the resulting tools and methodology and to transfer the expertise to industry.Read moreRead less
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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