MRMOGA: parallel evolutionary multiobjective optimization using multiple resolutions

Whereas multiobjective evolutionary algorithms have reached certain effectiveness in solving many real-world problems efficiency still remains as an open problem. One choice to reduce the execution time of the multiobjective evolutionary algorithms is their parallelization. This paper introduces a p...

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Bibliographic Details
Published in2005 IEEE Congress on Evolutionary Computation Vol. 3; pp. 2294 - 2301 Vol. 3
Main Authors Lopez Jaimes, A., Coello Coello, C.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Aerospace industry
Algorithm design and analysis
Design optimization
Encoding
Evolutionary computation
Genetic algorithms
Master-slave
Parallel processing
Tin
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Summary:Whereas multiobjective evolutionary algorithms have reached certain effectiveness in solving many real-world problems efficiency still remains as an open problem. One choice to reduce the execution time of the multiobjective evolutionary algorithms is their parallelization. This paper introduces a parallel MOEA which is based on the island model with heterogeneous nodes. This algorithm is characterized by encoding the solutions using a different resolution for each island. In this way, the search space is divided into well-defined overlapped regions in decision variable space.
ISBN:0780393635
9780780393639
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2005.1554980