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Communication dans un congrès

Optimal One-Max Strategy with Dynamic Island Models

Abstract :

In this paper, we recall the dynamic island model concept, in order to dynamically select local search operators within a multi-operator genetic algorithm. We use a fully-connected island model, where each island is assigned to a local search operator. Selection of operators is simulated by migration steps, whose policies depend on a learning process. The efficiency of this approach is assessed in comparing, for the One-Max Problem, theoretical and ideal results to those obtained by the model. Experiments show that the model has the expected behavior and is able to regain the optimal local search strategy for this well-known problem.

Type de document :
Communication dans un congrès
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Soumis le : jeudi 14 octobre 2021 - 16:12:14
Dernière modification le : mercredi 20 octobre 2021 - 03:19:09
Archivage à long terme le : : samedi 15 janvier 2022 - 19:22:56


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Adrien Goëffon, Frédéric Lardeux. Optimal One-Max Strategy with Dynamic Island Models. 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI, 2011, Boca Raton, United States. pp.485-488, ⟨10.1109/ICTAI.2011.79⟩. ⟨hal-03255426⟩



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