On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Introduction to Algorithms
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Crossover is provably essential for the Ising model on trees
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Runtime Analysis of the (μ+1) EA on Simple Pseudo-Boolean Functions
Evolutionary Computation
A building-block royal road where crossover is provably essential
Proceedings of the 9th annual conference on Genetic and evolutionary computation
On the scalability of parallel genetic algorithms
Evolutionary Computation
Analysis of diversity-preserving mechanisms for global exploration*
Evolutionary Computation
Real royal road functions-where crossover provably is essential
Discrete Applied Mathematics - Special issue: Boolean and pseudo-boolean funtions
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
Using markov-chain mixing time estimates for the analysis of ant colony optimization
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
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
DAMS: distributed adaptive metaheuristic selection
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Analysis of speedups in parallel evolutionary algorithms for combinatorial optimization
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Homogeneous and heterogeneous island models for the set cover problem
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
When do evolutionary algorithms optimize separable functions in parallel?
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
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Parallelization is becoming a more and more important issue for solving difficult optimization problems. Various implementations of parallel evolutionary algorithms (EAs) have been applied in the past decades. Island models combine phases of independent evolution with migration where genetic information is spread out to neighbored islands. Compared to panmictic models, this mechanism can lead to an increased diversity within the population. We perform a first rigorous runtime analysis for island models and construct a function where phases of independent evolution as well as communication among the islands is essential. A simple island model with migration finds a global optimum in polynomial time, while panmictic populations as well as island models without migration need exponential time, with very high probability. Our results lead to new insights on the usefulness of migration and contribute to the theoretical foundation of parallel EAs