9 citations · 15 across the 6 of their papers we have counts for
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cs.NE2021★ 3 cited
A Frequency-based Parent Selection for Reducing the Effect of Evaluation Time Bias in Asynchronous Parallel Multi-objective Evolutionary Algorithms
Tomohiro Harada
Parallel evolutionary algorithms (PEAs) have been studied for reducing the execution time of evolutionary algorithms by utilizing parallel computing. An asynchronous PEA (APEA) is…
cs.NE2021★ 9 cited
A Fresh Approach to Evaluate Performance in Distributed Parallel Genetic Algorithms
Tomohiro Harada, Enrique Alba, Gabriel Luque
This work proposes a novel approach to evaluate and analyze the behavior of multi-population parallel genetic algorithms (PGAs) when running on a cluster of multi-core processors.…