simulated annealing code minimize fitness function in matlab

main.m
% Fitness function
fitness = @(x) (x-5)^2;

% Parameters
initialSolution = 0; % Initial solution
initialTemperature = 100; % Initial temperature
coolingRate = 0.95; % Cooling rate
iterations = 100; % Number of iterations

% Initialize solution
bestSolution = initialSolution;
bestFitness = fitness(bestSolution);

% Main loop
temperature = initialTemperature;
for i = 1:iterations
    % Generate a neighboring solution
    neighborSolution = bestSolution + randn();
    neighborFitness = fitness(neighborSolution);
    
    % Determine if the neighbor is accepted
    if neighborFitness < bestFitness
        bestSolution = neighborSolution;
        bestFitness = neighborFitness;
    else
        acceptanceProbability = exp((bestFitness - neighborFitness) / temperature);
        if rand() < acceptanceProbability
            bestSolution = neighborSolution;
            bestFitness = neighborFitness;
        end
    end
    
    % Update temperature
    temperature = temperature * coolingRate;
end

% Display the result
disp(['Best solution: ' num2str(bestSolution)]);
disp(['Fitness value: ' num2str(bestFitness)]);
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