Cellular evolutionary algorithm

Cellular evolutionary algorithm

A cellular evolutionary algorithm (cEA) is a kind of evolutionary algorithm (EA) in which individuals cannot mate arbitrarily, but every one interacts with its closer neighbors on which a basic EA is applied (selection, variation, replacement).

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enA cellular evolutionary algorithm (cEA) is a kind of evolutionary algorithm (EA) in which individuals cannot mate arbitrarily, but every one interacts with its closer neighbors on which a basic EA is applied (selection, variation, replacement).
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CEA neighborhood types.png
Evolution of several cEAs.png
Ratio concept in cEAs.png
Has abstract
enA cellular evolutionary algorithm (cEA) is a kind of evolutionary algorithm (EA) in which individuals cannot mate arbitrarily, but every one interacts with its closer neighbors on which a basic EA is applied (selection, variation, replacement). The cellular model simulates natural evolution from the point of view ofthe individual, which encodes a tentative (optimization, learning, search) problem solution. The essential idea of this model is to provide the EA populationwith a special structure defined as a connected graph, in which each vertex is an individual who communicates with hisnearest neighbors. Particularly, individuals are conceptually set in a toroidalmesh, and are only allowed to recombine with close individuals. This leads usto a kind of locality known as isolation by distance. The set of potential matesof an individual is called its neighborhood. It is known that, in this kindof algorithm, similar individuals tend to cluster creating niches, and these groupsoperate as if they were separate sub-populations (islands). Anyway, there is noclear borderline between adjacent groups, and close niches could be easilycolonized by competitive niches and maybe merge solution contents during the process. Simultaneously,farther niches can be affected more slowly.
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Cellular evolutionary algorithm
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enCellular evolutionary algorithm
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atarazanas.sci.uma.es/docs/articulos/16603096.pdf
atarazanas.sci.uma.es/docs/tesisuma/1661480x.pdf
www.springer.com/business/operations+research/book/978-0-387-77609-5
www.lcc.uma.es/~eat/pdf/comcom07.pdf
neo.lcc.uma.es/cEA-web/
neo.lcc.uma.es
www.researchgate.net/profile/Andrea_Tettamanzi/publication/3418844_Selection_Intensity_in_Cellular_Evolutionary_Algorithms_for_Regular_Lattices/links/00463525c395463b1b000000/Selection-Intensity-in-Cellular-Evolutionary-Algorithms-for-Regular-Lattices.pdf
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Category:Evolutionary algorithms
Cellular automata
Cellular automaton
Dual-phase evolution
Enrique Alba
Evolutionary algorithm
File:CEA neighborhood types.png
File:Evolution of several cEAs.png
File:Ratio concept in cEAs.png
FPGAs
GPUs
Metaheuristic
Parallel metaheuristic
Parallel metaheuristics
SameAs
4geak
Cellular evolutionary algorithm
m.0h95zwm
Q5058361
Subject
Category:Evolutionary algorithms
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Evolution of several cEAs.png?width=300
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