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Amr Soghier Research
Interests Publications
Research Interests
Hyper-heuristics
The current state of the art in decision support
and search methodologies tends to focus on bespoke problem specific systems.
Indeed, there are many examples of powerful and innovative search
methodologies which have been tailored for specific applications and which
underpin highly effective decision support systems.
Over the last 20 years or so, there has been
significant scientific progress in building search methodologies and in
tailoring those methodologies (usually through hybridisation with problem
specific methods and information) for a very wide range of application
areas. Such methodologies can be extremely effective in the hands of an
expert but they require specialist human knowledge to be applied effectively
in complex real world problem solving environments.
The goal of developing automated systems to
replace the human expert in this role is only just beginning to be seriously
addressed by the scientific community. The challenge of developing systems
to intelligently select, evolve and develop search methods is an extremely
ambitious and demanding research goal. The level of adventure should not be
underestimated. The goal of exploring the boundaries between what is
possible and what is not (with respect to the automation of the heuristic
design process) represents one of the most important current research
challenges to face the search and decision support community.
The main aim of this major and far reaching
programme of research is to address this challenge by investigating a wide
range of promising and adventurous research directions in an integrated and
co-ordinated manner. The successful development of automated systems to
generate heuristic methods would underpin the next generation of search/optimisation
systems that would be able to operate at a fundamentally more general level
than current understanding can support. The aim is to develop systems which
can operate upon a wider range of problems and problem instances than is
possible with today's technology by automatically tailoring heuristics to
particular problems and problem instances.
Today, this process can only be effectively
carried out by human experts. Of course, we know (from the No Free Lunch
theorem and related work) that it will not be possible to build a completely
general search method. However, we also know (from work carried out by
ourselves and others) that it is possible to generate methods that are more
general than the current state of the art. The question of how general we
can make search systems is very much an open question and it is one that we
will explore in this research programme. The emphasis will not follow
conventional current thinking by concentrating on the development of systems
to solve particular search/optimisation problems. Instead this major
scientific undertaking will investigate the possibility of developing
adaptive systems which can react to the conditions and the environment of
the particular decision support problem in hand.
The potential benefits of success in such a
radical undertaking are enormous and permeate not only the disciplines of
Artificial Intelligence and Operational Research but also the various
disciplines that draw on and contribute to them. These include Computer
Science, Mathematics, Business, Engineering, Computational Chemistry,
Medicine, Architecture (space planning), Bioinformatics, Manufacturing and
all areas of Management. The research will also impact upon automated
heuristic selection and design across many diverse applications such as
scheduling, timetabling, cutting/packing, protein folding, catalyst
optimisation, medical decision making and others.
This research initiative will enable us to explore
risky and unconventional ideas across a range of disciplines and research
council remits in a way that is not possible with standard grants and it
will allow us to flexibly redirect our efforts across application areas as
well as disciplines to explore ideas as they emerge.
Publications
Amr Soghier Research
Interests Publications
E.K. Burke, R. Qu and A. Soghier, Adaptive Selection of Heuristics within a GRASP for Exam Timetabling Problems, to appear at The 4th Multidisciplinary International Scheduling: Theory and Applications 2009 (MISTA 2009), 10-12 August 2009, Dublin, Ireland.
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