Topologies, migration rates, and multi-population parallel genetic algorithms
E Cant�-Paz�- Proceedings of the 1st Annual Conference on Genetic�…, 1999 - dl.acm.org
Proceedings of the 1st Annual Conference on Genetic and Evolutionary�…, 1999•dl.acm.org
This paper presents a study of parallel genetic algorithms (GAs) with multiple populations
(also called demes or islands). The study makes explicit the relation between the probability
of reaching a desired solution with the deme size, the migration rate, and the degree of the
connectivity graph. The paper considers arbitrary topologies with a fixed number of
neighbors per deme. The demes evolve in isolation until each converges to a unique
solution. Then, the demes exchange an arbitrary number of individuals and restart their�…
(also called demes or islands). The study makes explicit the relation between the probability
of reaching a desired solution with the deme size, the migration rate, and the degree of the
connectivity graph. The paper considers arbitrary topologies with a fixed number of
neighbors per deme. The demes evolve in isolation until each converges to a unique
solution. Then, the demes exchange an arbitrary number of individuals and restart their�…
This paper presents a study of parallel genetic algorithms (GAs) with multiple populations (also called demes or islands). The study makes explicit the relation between the probability of reaching a desired solution with the deme size, the migration rate, and the degree of the connectivity graph. The paper considers arbitrary topologies with a fixed number of neighbors per deme. The demes evolve in isolation until each converges to a unique solution. Then, the demes exchange an arbitrary number of individuals and restart their execution. An accurate deme-sizing equation is derived, and it is used to determine the optimal configuration of an arbitrary number of demes that minimizes the execution time of the parallel GA.
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