mixed integer multi objective optimization using gamultiobj ; how do i code the custom mutation function to satisfy linear constraints? cuz i sovle with the dafault mutationadaptfeasible but constraint violated.this link is custom gaussian, cant help

function mutationChildren = int_mutation(parents, options, GenomeLength, ...

    ~, state, ~, ~)

% Function that creates the mutated children using the Gaussian
% distribution. It does not satisfy linear constraints!

%IntCon constraints
IntCon = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16];

shrink = 0.01; 
scale = 1;
scale = scale - shrink * scale * state.Generation/options.Generations;
range = options.PopInitRange;
lower = range(1,:);
upper = range(2,:);
scale = scale * (upper - lower);
mutationPop =  length(parents);

mutationChildren =  repmat(lower,mutationPop,1) +  ...
    repmat(scale, mutationPop,1) .* rand(mutationPop, GenomeLength);

x = rand;
if x>=0.5
    mutationChildren(:, IntCon) = floor(mutationChildren(:,IntCon));
else
    mutationChildren(:, IntCon) = ceil(mutationChildren(:,IntCon));
end

mutationChildren = checkboundsIntGA(mutationChildren, range);

i have a mixed integer multiobjective(3 objectives) linear optimization problem with linear constraints. how do i solve this using gamultiobj?how do i code the custom mutation function to satisfy linear constraints? because i sovle with the dafault adaptive feasible ('mutationadaptfeasible') but the solution did not satisfy my linear constraints. the solution provided in the link below is the customized ('mutationgaussian') which cant satisfy linear constraints.

https://www.mathworks.com/matlabcentral/answers/103369-is-it-possible-to-solve-a-mixed-integer-multi-objective-optimization-problem-using-global-optimizati