Mixed-Integer Surrogate Optimization

This example shows how to solve an optimization problem that involves integer variables. Beginning in R2019b, surrogateopt accepts integer constraints. In this example, find the point x that minimizes the multirosenbrock function over integer-valued arguments ranging from –3 to 6 in ten dimensions. The multirosenbrock function is a poorly scaled function that is difficult to optimize. Its minimum value is 0, which is attained at the point [1,1,...,1].

rng(1,'twister') % For reproducibility
nvar = 10; % Any even number
lb = -3*ones(1,nvar);
ub = 6*ones(1,nvar);
fun = @multirosenbrock;
intcon = 1:nvar; % All integer variables
[sol,fval] = surrogateopt(fun,lb,ub,intcon)

Surrogateopt stopped because it exceeded the function evaluation limit set by 
'options.MaxFunctionEvaluations'.
sol = 1×10

     1     1     1     1     1     1     1     1     1     1

fval = 0

In this case, surrogateopt finds the correct solution.

See Also

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