Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
The influence of migration sizes and intervals on island models
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Parallel Evolutionary Computations (Studies in Computational Intelligence)
Parallel Evolutionary Computations (Studies in Computational Intelligence)
A building-block royal road where crossover is provably essential
Proceedings of the 9th annual conference on Genetic and evolutionary computation
An analysis of island models in evolutionary computation
An analysis of island models in evolutionary computation
The benefit of migration in parallel evolutionary algorithms
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Experimental supplements to the theoretical analysis of migration in the Island model
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
General scheme for analyzing running times of parallel evolutionary algorithms
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Approximating covering problems by randomized search heuristics using multi-objective models*
Evolutionary Computation
Adaptive population models for offspring populations and parallel evolutionary algorithms
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
On the effectiveness of crossover for migration in parallel evolutionary algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Evolutionary algorithms and dynamic programming
Theoretical Computer Science
Analysis of speedups in parallel evolutionary algorithms for combinatorial optimization
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
| Hi-index | 0.00 |
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.