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.
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.
Page maintained by: Edward Tsang
Constraint Research Group,
Department of Computer Science,
University of Essex
Updated: 12 August 2005
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