Chromosome (evolutionary algorithm): Difference between revisions

Revision as of 03:08, 2 February 2006

Revision as of 09:33, 10 April 2006

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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.

2006

[[Category:Genetic algorithms]]