Implement parameter constraint for surrogateopt

2 次查看(过去 30 天)
Hello,
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);
params(4)-params(3)];
ceq = [];
end
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;
else
f.Fval = objFun(param);
end
f.Ineq = [params(2)-params(1);
params(4)-params(3)];
end
Or is there a smarter and more efficient way?
I'm looking forward to any hint on how to improve this!

采纳的回答

Alan Weiss
Alan Weiss 2021-10-29
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
end
Alan Weiss
MATLAB mathematical toolbox documentation
  3 个评论
Alan Weiss
Alan Weiss 2021-10-29
Indeed, for R2021a the linear constraints are always satisfied. For R2020a, the constraints can be violated.
Alan Weiss
MATLAB mathematical toolbox documentation

请先登录,再进行评论。

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Solver Outputs and Iterative Display 的更多信息

产品


版本

R2020b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by