optimizer_ga: Genetic Algorithm Optimizer

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Genetic Algorithm Optimizer

Description

Creates a real-coded Genetic Algorithm optimizer object.

Usage

optimizer_ga(
  pop_size = 30,
  max_iter = 100,
  crossover_rate = 0.8,
  mutation_rate = 0.1,
  mutation_sd = 0.1,
  elitism = TRUE,
  selection = "tournament",
  tournament_size = 2
)

Arguments

pop_size	Population size.
max_iter	Maximum number of iterations.
crossover_rate	Probability of crossover.
mutation_rate	Probability of mutating each parameter.
mutation_sd	Standard deviation of Gaussian mutation noise.
elitism	Logical. Whether to preserve the best solution in each generation.
selection	Selection method. Currently only "tournament" is supported.
tournament_size	Number of individuals used in tournament selection.

Value

An object of class "met_optimizer".

References

Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA.

Montana, D. J., and Davis, L. (1989). Training Feedforward Neural Networks Using Genetic Algorithms. Proceedings of the 11th International Joint Conference on Artificial Intelligence, 762–767.

Examples

optimizer_ga()

metANN documentation built on May 16, 2026, 1:06 a.m.