Multiobjective meta level optimization of a load balancing evolutionary algorithm
EMO'03: Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Pages 177 - 191
Abstract
For any optimization algorithm tuning the parameters is necessary for effective and efficient optimization. We use a meta-level evolutionary algorithm for optimizing the effectiveness and efficiency of a load-balancing evolutionary algorithm. We show that the generated parameters perform statistically better than a standard set of parameters and analyze the importance of selecting a good region on the Pareto Front for this type of optimization.
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Published In
April 2003
811 pages
ISBN:3540018697
Sponsors
- Fundação Luso-Americana para o Desenvolvimento
- Fundação Calouste Gulbenkian
- Fundação para a Ciência e a Tecnologia
- Fundação Oriente
- Universidade do Algarve
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 08 April 2003
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