simulated annealing code in matlab

main.m
% Function to be minimized
fun = @(x) x^2 - 4*x + 3;

% Define the search space
x_lower = -10;
x_upper = 10;

% Simulated Annealing parameters
initial_temperature = 100;
cooling_ratio = 0.95;
min_temperature = 1e-6;
max_iterations = 1000;

% Initialize variables
temperature = initial_temperature;
current_solution = (x_upper - x_lower) * rand() + x_lower;
best_solution = current_solution;

% Start simulated annealing
while temperature > min_temperature
    for i = 1:max_iterations
        % Generate a new candidate solution
        new_solution = current_solution + (rand() - 0.5) * temperature;
        
        % Calculate the energy difference
        energy_difference = fun(new_solution) - fun(current_solution);
        
        % Accept the new solution if it is better or with a certain probability
        if energy_difference < 0 || exp(-energy_difference / temperature) > rand()
            current_solution = new_solution;
        end
        
        % Update the best solution found so far
        if fun(current_solution) < fun(best_solution)
            best_solution = current_solution;
        end
    end
    
    % Cool down the temperature for the next iteration
    temperature = temperature * cooling_ratio;
end

% Output the best solution found
fprintf('Best solution: %f\n', best_solution);
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