How to set up variable with only several states in the genetic algorithm

How to set up the constrain simple_constraint(x) in the genetic algorim optimization with variable x(2) and x(3)that can take only four values 0 1 2 4 ?

ObjectiveFunction = @simple_fitness;
nvars = 3;    % Number of variables
LB = [0 0 0];   % Lower bound
UB = [1 4 4];  % Upper bound
ConstraintFunction = @simple_constraint;
[x,fval] = ga(ObjectiveFunction,nvars,[],[],[],[],LB,UB, ...
    ConstraintFunction)
function y = simple_fitness(x)
    y = (x(1)^3*cos(x(2)*pi/2+0.9)*sin(x(2)*pi/2+0.2)+cos(x(3)*pi/2+0.3)) ;
    function [c, ceq] = simple_constraint(x)
   c = [];
   ceq = [];

Answer 1

[Star Strider]

See the documentation section on Minimize a Nonlinear Function with Integer Constraints and then set the bounds on ‘x(2)’ and ‘x(3)’ appropriately. (I have some experience with ga, however I have not used integer constraints to solve any problem.)

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