Week 5 - Genetic Algorithm

% Genetic Algorithm Optimization of the Stalagmite Function

% Define the Stalagmite Function

function f = stalagmite(x)

f = (sin(5.1*pi*x(1) + 0.5*pi))^6 * (sin(5.1*pi*x(2) + 0.5*pi))^6;

end

% Main Script

clc;

clear;

close all;

% Set the random seed for reproducibility

rng(1);

% Define the fitness function as a handle to the stalagmite function

fitnessFunction = @(x) -stalagmite(x); % Minimize negative to maximize original

% Number of variables

nvars = 2;

% Set options for the Genetic Algorithm

options = optimoptions('ga', 'PlotFcn', @gaplotbestf, 'MaxGenerations', 100, 'Display', 'iter');

% Run the Genetic Algorithm

[x, fval] = ga(fitnessFunction, nvars, [], [], [], [], [0 0], [1 1], [], options);

% Display the results

disp(['Global Maximum found at: x1 = ', num2str(x(1)), ', x2 = ', num2str(x(2))]);

disp(['Function value at Global Maximum: ', num2str(-fval)]);

% Plot the Stalagmite Function

figure;

fsurf(@stalagmite, [0 1 0 1]);

title('Stalagmite Function');

xlabel('x1');

ylabel('x2');

zlabel('f(x)');