replacement: Replacing non-selected individual(s)

In genetic.algo.optimizeR: Genetic Algorithm Optimization

Replacing non-selected individual(s)

Description

This function replace the individual(s) that was/were not selected (i.e. not the best fit) 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.

Usage

replacement(population, offspring, num_to_replace)

Arguments

population	The list of individuals of the population
offspring	The list of offspring.
num_to_replace	The number of selected individuals that should be replaced in the population.

Value

The output expected should be a list of selected individuals that fit the best with the predefined aim.

Author(s)

Dany Mukesha

Examples

# example of usage
population <- c(1, 3, 0)

# Evaluate fitness
fitness <- genetic.algo.optimizeR::evaluate_fitness(population)
print("Evaluation:")
print(fitness)

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

# Crossover and mutation
offspring <- genetic.algo.optimizeR::crossover(selected_parents, offspring_size = 2)
mutated_offspring <- mutation(offspring, mutation_rate = 0) # (no mutation in this example)
print(mutated_offspring)

# Replacement
population <- genetic.algo.optimizeR::replacement(population, mutated_offspring, num_to_replace = 1)
print("Replacement:")
print(population)

genetic.algo.optimizeR documentation built on Oct. 10, 2024, 5:07 p.m.