[MATLAB] Algoritma Genetika #2 - Membuat Populasi

Introduction

This tutorial will guide you through creating a population in MATLAB using genetic algorithms. By the end of this guide, you will understand how to implement a basic population structure using MATLAB's struct data type, which is essential for developing genetic algorithms.

Step 1: Setting Up MATLAB Environment

• Open MATLAB on your computer.
• Ensure you have the necessary toolboxes installed for working with genetic algorithms.
• Familiarize yourself with the MATLAB interface, focusing on the Editor and Command Window.

Step 2: Creating the Population Structure

• Define the population size. For example, let’s create a population of 10 individuals.
• Use the struct data type to create a structure that will hold each individual's information. This structure can include fields such as genes, fitness, and id.

populationSize = 10; % Define the size of the population
population = struct('id', [], 'genes', [], 'fitness', []); % Initialize the population structure

Step 3: Initializing Individual Genes

• For each individual in the population, randomly generate genes. The genes can be represented as binary strings or any other format suitable for your problem.

for i = 1:populationSize
    population(i).id = i; % Assign an ID to each individual
    population(i).genes = randi([0 1], 1, 5); % Example: Binary genes of length 5
end

Step 4: Calculating Fitness Values

• Implement a fitness function that evaluates how well each individual performs in the context of your genetic algorithm. This function could be specific to the problem you are solving.

for i = 1:populationSize
    population(i).fitness = evaluateFitness(population(i).genes); % Custom function to evaluate fitness
end

• Define the evaluateFitness function according to your needs.

function fitness = evaluateFitness(genes)
    % Example fitness calculation (customize as needed)
    fitness = sum(genes); % Simple sum of genes as fitness
end

Step 5: Displaying the Population

• After initializing the population and calculating fitness, display the population to verify that everything is set up correctly.

disp(population);

Conclusion

In this tutorial, you learned how to create a population for genetic algorithms in MATLAB. You set up the environment, defined the population structure, initialized genes, calculated fitness values, and displayed the population.

Next steps could include evolving the population through selection, crossover, and mutation processes, which are fundamental aspects of genetic algorithms. For further learning, consider exploring the provided playlists and resources on MATLAB and genetic algorithms.