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Showing content from https://danymukesha.github.io/genetic.algo.optimizeR/reference/selection.html below:

Selecting the fitting the population — selection • genetic.algo.optimizeR

The function described below selects the individuals that fit the best based on the predefined condition(aim/objective).
e.g.: To optimize the function \(f(x) = x^2 - 4x + 4\) to find the value of \(x\) that minimizes the function. \(x\): represents a possible value the an individual from the population can have.

selection(population, fitness, num_parents)

population

The list of individuals of the population

fitness

The list of individuals(value) obtained from the function of genetic.algo.optimizeR namely `evaluate_fitness`.

num_parents

The number of selected individuals that fit the best with the predefined aim.

The output expected should be a list of selected individuals that fit the best with the predefined condition(aim/objective).

# example of usage
library(genetic.algo.optimizeR)

population <- c(1, 3, 0)

# Evaluate fitness
fitness <- genetic.algo.optimizeR::evaluate_fitness(population)
print("Evaluation:")
#> [1] "Evaluation:"
print(fitness)
#> [1] 1 1 4

# Selection
selected_parents <- genetic.algo.optimizeR::selection(population, fitness, num_parents = 2)
print("Selection:")
#> [1] "Selection:"
print(selected_parents)
#> [1] 1 3

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