Introduction to genetic.algo.optimizeR"
In genetic.algo.optimizeR: Genetic Algorithm Optimization

knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>"
)

Overview

This vignette demonstrates how to use the genetic.algo.optimizeR package to optimize the function ( f(x) = x^2 - 4x + 4 ) using a genetic algorithm.

Aim

Optimize the function ( f(x) = x^2 - 4x + 4 ) to find the value of ( x ) that minimizes the function.

Method

Initial Population

We start with a population of three individuals: ( x_1 = 1 ), ( x_2 = 3 ), and ( x_3 = 0 ).

# devtools::install_github("danymukesha/genetic.algo.optimizeR", upgrade = c("never"),)
library(genetic.algo.optimizeR)

# Initialize population
population <- initialize_population(population_size = 3, min = 0, max = 3)
population

Evaluation

We evaluate the fitness of each individual by calculating ( f(x) ) for each ( x ) value:

# Evaluate fitness
fitness <- evaluate_fitness(population)
fitness

Selection

We select individuals ( x_1 ) and ( x_2 ) as parents for crossover because they have higher fitness.

# Perform selection
selected_parents <- selection(population, fitness, num_parents = 2)
selected_parents

Crossover and Mutation

We perform crossover and mutation on the selected parents to generate offspring: ( x_1' = 1 ), ( x_2' = 3 ).

# Perform crossover
offspring <- crossover(selected_parents, offspring_size = 2)
offspring

# Perform mutation
mutated_offspring <- mutation(offspring, mutation_rate = 0.1)
mutated_offspring

Replacement

We replace individual ( x_3 ) with offspring ( x_1' ), maintaining the population size.

# Replace individuals in the population
new_population <- replacement(population, mutated_offspring, num_to_replace = 1)
new_population

# Termination
# Repeat the above steps(from Evaluation) for multiple generations or until a termination condition is met.

Warp-Up

This vignette demonstrates the usage of the genetic.algo.optimizeR package to optimize the given function using a genetic algorithm. Users can follow similar steps to optimize other functions or customize the parameters as needed.