how to set constraints of the var model in genetic algorithm for 9 variables in matlab

main.m
% Define the number of variables
nVars = 9;

% Define the lower and upper bounds for each variable
lowerBounds = [0, 0, 0, 0, 0, 0, 0, 0, 0];
upperBounds = [1, 1, 1, 1, 1, 1, 1, 1, 1];

% Create the options structure
options = gaoptimset('PopulationType', 'doubleVector', ...
    'PopulationSize', 50, ...
    'Generations', 100, ...
    'FitnessLimit', 0, ...
    'StallGenLimit', 50, ...
    'PlotFcns', @gaplotbestf, ...
    'Display', 'final', ...
    'UseParallel', 'always', ...
    'Vectorized', 'off', ...
    'FitnessScalingFcn', @fitscalingprop, ...
    'SelectionFcn', @selectionroulette, ...
    'CrossoverFcn', @crossoverscattered, ...
    'MutationFcn', @mutationuniform, ...
    'TolFun', 1e-6, ...
    'TolCon', 1e-6, ...
    'ConstraintTolerance', 1e-6);

% Set the custom bounds
options.lb = lowerBounds;
options.ub = upperBounds;

% Run the genetic algorithm
[x, fval] = ga(@(x) myFitnessFcn(x), nVars, [], [], [], [], ...
    options.lb, options.ub, [], [], options);

% Define the fitness function
function f = myFitnessFcn(x)
    % Your custom fitness function code here
end
1097 chars
38 lines