Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms
Journal of Heuristics
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Diversity-Guided Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
The influence of migration sizes and intervals on island models
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
An adaptive pursuit strategy for allocating operator probabilities
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The speciating island model: an alternative parallel evolutionary algorithm
Journal of Parallel and Distributed Computing - Special issue on parallel bioinspired algorithms
Extreme Value Based Adaptive Operator Selection
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Parameter Setting in Evolutionary Algorithms
Parameter Setting in Evolutionary Algorithms
Genotypic differences and migration policies in an island model
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Relevance estimation and value calibration of evolutionary algorithm parameters
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
ParamILS: an automatic algorithm configuration framework
Journal of Artificial Intelligence Research
Autonomous operator management for evolutionary algorithms
Journal of Heuristics
A dynamic Island-based genetic algorithms framework
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
DAMS: distributed adaptive metaheuristic selection
Proceedings of the 13th annual conference on Genetic and evolutionary computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Ensemble fuzzy rule-based classifier design by parallel distributed fuzzy GBML algorithms
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
Non stationary operator selection with island models
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Is the meta-EA a viable optimization method?
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In this paper we propose a generic framework for Dynamic Island Models, which can be used as an original approach for the adaptive selection of operators in evolutionary algorithms. Assigning a variation operator to each island, we show that the dynamic regulation of migrations, which takes into account the pertinence of recent migrations, distributes the individuals on the most promising islands, i.e., the most efficient operators, at each stage of the search. The efficiency of this approach is assessed on the One-Max problem by comparing theoretical expected results to those obtained by our dynamic island model. Experiments show that the model provides the expected behavior.