Chromosome (evolutionary algorithm): Difference between revisions

Revision as of 02:16, 4 May 2004

Revision as of 04:07, 31 July 2004

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A genetic algorithm creates many chromosomes, either randomly or by design, as an initial population. These chromosomes are each evaluated by the [[fitness function]], which ranks them according to how good their solution is. The chromosomes which produced the best solutions, relatively speaking within the population, are allowed to breed, called [[crossover (genetic algorithm)|crossover]]. The best chromosomes' data is mixed, hopefully producing a better next generation.

==DataSee Typesalso==

*[[chromosome]]

Different data types have proven better suited to different problem domains.

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''Please add to this; list data types and problem domains which they are particularly applicable to.''

==See also==

* [[Chromosome|Chromosome (biology)]]

[[Category:Genetic algorithms]]

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