The Research Agenda, a non-technical description:
Many real-life problems involve more than one objective.
For example, investors may balance between return and risk (normally
the higher the return an investment gives, the higher its risk).
Production managers have to balance between cost, quality,
staff morale, etc. In optimization research, multi-objectives
are sometimes combined into one (for example, by giving weights to
individual objectives). However, in many cases, it is difficult
to assign such weights, which motivates the field of
multi-objective optimization.
Our Expertise:
This research tackles the multi-objective optimization problem as they are
without combining objectives.
Generic methods are being developed in this project, using on
our expertise in optimization,
Estimation of Distribution Algorithms
(a branch of evolutionary computation)
and
heuristic search.
Selected Publications:
Zhou et al
Page maintained by: Edward Tsang
Constraint Research Group,
Department of Computer Science,
University of Essex
Updated: 12 August 2005
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