Genetic Algorithms
1
Start Set: Npop, Nmat, Nmut, Nger Initial random population Fitness evaluation Penalties Selection Crossover Mutation i=Nger End Yes No i-Population Genetic algorithms (GA), which were invented by John Holland in 1975, are a heuristic method based on “Survival of the fittest”. They combine the persistence of the strongest with a random exchange of information arranged to form a search algorithm. In every iteration, a new generation is created using data of the fittest previous set. However, genetic algorithms are not just a random path, they efficiently take advantage of historical information to speculate new search points with an expected improvement in performance.
description
Diagrama de flujo de un algoritmo genético y resumen
Transcript of Genetic Algorithms
StartSet: Npop, Nmat, Nmut,
Nger
Initial random population
Fitness evaluation
Penalties
Selection
Crossover
Mutation
i=Nger
End
Yes
No
i-Population
Genetic algorithms (GA), which were invented by John Holland in 1975, are a heuristic method based
on “Survival of the fittest”. They combine the persistence of the strongest with a random exchange
of information arranged to form a search algorithm. In every iteration, a new generation is created
using data of the fittest previous set. However, genetic algorithms are not just a random path, they
efficiently take advantage of historical information to speculate new search points with an expected
improvement in performance.
