Implement parameter constraint for surrogateopt

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Elsa Bunz
Elsa Bunz 2021 年 10 月 27 日
コメント済み: Elsa Bunz 2021 年 10 月 29 日
I want to run an optimisation using surrogateopt and I have the constraint, that certain parameters can't be smaller than others. So, I guess for other methods my constraint function would look like this (?):
params = [param1, param2, param3, param4]
function [c, ceq] = simple_constraint(params)
c = [params(2)-params(1);
ceq = [];
As far as I understood in surrogateopt the constraints are set in the objective function.
What is the best way to implement these parameter constraints which are independent of the objective function value?
Just setting and arbitrary high value as value of the objective function? So, something like this:
function f = objFun_surrogateopt(param)
if params(2)> params(1) || params(4) > params(3)
f.Fval = 1000;
f.Fval = objFun(param);
f.Ineq = [params(2)-params(1);
Or is there a smarter and more efficient way?
I'm looking forward to any hint on how to improve this!


Alan Weiss
Alan Weiss 2021 年 10 月 29 日
The answer depends on your MATLAB version. As the Release Notes show, linear constraints were introduced in R2021a, nonlinear constraints were initroduced in R2020a.
  • With R2021a or later, param(2) >= param(1) is equivalent to the linear constraint
A = [1 -1 0 0 0];
b = 0; % This means x(1) - x(2) <= 0, or x(1) <= x(2)
  • With R2020a or R2020b, represent the constraint as a nonlinear inequality constraint:
function F = objcon(x)
F.Ineq = x(1) - x(2);
F.Fval = % your objective function here
Alan Weiss
MATLAB mathematical toolbox documentation
  3 件のコメント
Elsa Bunz
Elsa Bunz 2021 年 10 月 29 日
Okay, thanks a lot for the clarification!


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