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 Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Parallel Combinatorial Optimization (Wiley Series on Parallel and Distributed Computing)
Parallel Combinatorial Optimization (Wiley Series on Parallel and Distributed Computing)
Adjacency list matchings: an ideal genotype for cycle covers
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Speeding up evolutionary algorithms through asymmetric mutation operators
Evolutionary Computation
Expected runtimes of evolutionary algorithms for the Eulerian cycle problem
Computers and Operations Research
Edge-based representation beats vertex-based representation in shortest path problems
Proceedings of the 12th annual conference on Genetic and 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
Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity
Bioinspired Computation in Combinatorial Optimization: Algorithms and Their Computational Complexity
Adaptive population models for offspring populations and parallel evolutionary algorithms
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
The use of tail inequalities on the probable computational time of randomized search heuristics
Theoretical Computer Science
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
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Evolutionary algorithms are popular heuristics for solving various combinatorial problems as they are easy to apply and often produce good results. Island models parallelize evolution by using different populations, called islands, which are connected by a graph structure as communication topology. Each island periodically communicates copies of good solutions to neighboring islands in a process called migration. We consider the speedup gained by island models in terms of the parallel running time for problems from combinatorial optimization: sorting (as maximization of sortedness), shortest paths, and Eulerian cycles. Different search operators are considered. The results show in which settings and up to what degree evolutionary algorithms can be parallelized efficiently. Along the way, we also investigate how island models deal with plateaus. In particular, we show that natural settings lead to exponential vs. logarithmic speedups, depending on the frequency of migration.