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 0 0 0 0 1 1 -1 1
fval = 6
In this case, surrogateopt does not find the correct solution.