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To
conduct interdisciplinary research in the area of systems modelling
and analysis for defence applications.
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SMAL
is a collaboration between the Faculty of Engineering and the Defence
Science and Technology Agency (DSTA) of the Ministry of Defence.
SMAL conducts multidisciplinary research on advanced systems modelling,
analysis, simulation and optimisation. Its research programmes emphasise
interdisciplinary approaches that combine techniques from operations
research, artificial intelligence, computational sciences and systems
sciences.
The laboratory has carried out research into military storage planning
and optimisation, project scheduling and manpower planning, scheduling
and reactive scheduling of multi-period tasks, applications of Bayesian
networks in military planning and operations analysis and development
of decision systems for network interdictions. It presently plays
a major role in hosting a major project funded under the Defence
Innovative Research Programme. The Advanced Planning & Decision
Systems Project was recently launched in collaboration with the
Decision Support Solutions Programme and the Knowledge-based Solutions
Division of DSTA.
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The
main goal of the project is to develop a set of advanced computational
techniques and algorithms that facilitate the building of advanced
planning systems for allocation of resources and intelligent decision
systems that are capable of responding to sensory inputs and providing
an optimal course of action to decision-makers in an uncertain and
dynamic environment.
The project will focus on two lines of investigation. The first
involves the development of algorithms for the rostering of workforce
to duties and equipment, using methods that combine the features
of column generation from operations research and constraint programming
from artificial intelligence. The second involves the development
of intelligent normative decision systems for automated reasoning
and decision-making in an uncertain and dynamic environment. These
systems will be capable of constructing situation-specific models
in response to sensory information. |
