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Cellular evolutionary algorithm
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Cellular evolutionary algorithm : ウィキペディア英語版
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).
The cellular model simulates Natural evolution from the point of view of
the individual, which encodes a tentative (optimization, learning, search) problem solution. The essential idea of this model is to provide the EA population
with a special structure defined as a connected graph, in which each vertex is an individual who communicates with his
nearest neighbors. Particularly, individuals are conceptually set in a toroidal
mesh, and are only allowed to recombine with close individuals. This leads us
to a kind of locality known as ''isolation by distance''. The set of potential mates
of an individual is called its ''neighborhood''. It is known that, in this kind
of algorithm, similar individuals tend to cluster creating niches, and these groups
operate as if they were separate sub-populations (islands). Anyway, there is no
clear borderline between adjacent groups, and close niches could be easily
colonized by competitive niches and maybe merge solution contents during the process. Simultaneously,
farther niches can be affected more slowly.
==Introduction==

A Cellular Evolutionary Algorithm (cEA) usually evolves a structured bidimensional
grid of individuals, although other topologies are also possible. In this grid, clusters of similar individuals are naturally created during evolution, promoting exploration in their boundaries, while exploitation is mainly performed by direct competition and merging inside them.
The grid is usually 2D toroidal structure, although
the number of dimensions can be easily extended (to 3D) or reduced (to 1D, e.g. a ring).
The neighborhood of a particular point of the grid (where an individual is
placed) is defined in terms of the ''Manhattan'' distance from it to others in the population. Each point of the grid has a neighborhood that overlaps the neighborhoods of nearby individuals. In the basic algorithm, all the neighborhoods have the same size and identical shapes. The two
most commonly used neighborhoods are L5, also called
''Von Neumann'' or NEWS (North, East, West and South), and C9, also known as ''Moore'' neighborhood. Here, ''L'' stands for ''Linear'' while ''C'' stands for ''Compact''.
In cEAs, the individuals can only interact with their neighbors in the reproductive
cycle where the variation operators are applied. This reproductive
cycle is executed inside the neighborhood of each individual and, generally,
consists in selecting two parents among its neighbors according to a certain
criterion, applying the variation operators to them (recombination and mutation
for example), and replacing the considered individual by the recently
created offspring following a given criterion, for instance, replace if the offspring
represents a better solution than the considered individual.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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