Homogeneous and Heterogeneous Island Models for the Set Cover Problem

We propose and analyse two island models that provably find good approximations for the SetCover problem. A homogeneous island model running parallel instances of the SEMO algorithm--following Friedrich et al. (Evolutionary Computation 18(4), 2010, 617-633)--leads to significant speedups over a single SEMO instance, but at the expense of large communication costs. A heterogeneous island model, where each island optimises a different single-objective fitness function, provides similar speedups at reduced communication costs. We compare different topologies for the homogeneous model and different migration policies for the heterogeneous one.

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