Matching island topologies to problem structure in parallel evolutionary algorithms

In the context of Parallel Evolutionary Algorithms, it has been shown that different population structures induce different search performances. Nevertheless, no work has shown a clear cut evidence that there is a correlation between the solver’s population structure and the problem’s network structure. In this work, we verify this correlation performing a clear and systematic analysis of a large set of population structures (based on the well known β-graphs and NK-landscape problems. Furthermore, we go beyond our findings in these idealised experiments by analysing the performance of variable-topology EAs on a dynamic real-world problem, the Multi-Skills Call Centre.

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