maximizing a function with a nonlinear constraint using fmincon
2 views (last 30 days)
Show older comments
Dear all,
I have a function 'fun' which I want to maximize with respect to four unknowns: x(1) x(2) x(3) and x(4)
under the constraint
exp(x(2))+exp(x(3))<0.99
So, I set up something like that
function [c,ceq] = mycon(x)
c= exp(x(2))+exp(x(3))-0.99;
ceq=[];
end
x0=[a ;b c; d] % the initial value
options=optimset( 'display','off'); % mainly use this
[xx,fval,exitflag,output,lambda,grad,HH]=fmincon('fun',x0,...
[],[],[],[],[],[],@mycon, options);
But I get this warning
Error using mycon
Too many input arguments.
Error in fmincon (line 622)
[ctmp,ceqtmp] = feval(confcn{3},X,varargin{:});
Error in dokimi_3 (line 96)
[xx,fval,exitflag,output,lambda,grad,HH]=fmincon('fun',x0,...
Caused by:
Failure in initial nonlinear constraint function evaluation. FMINCON cannot continue.
Any ideas what is wrong?
Thank you
3 Comments
Walter Roberson
on 21 Jan 2018
Is it possible that in your actual code that you passed something to fmincon after the options argument?
Accepted Answer
Matt J
on 21 Jan 2018
Edited: Matt J
on 21 Jan 2018
Rewrite mycon to have this form,
function [c,ceq] = mycon(x, y,mu, psi,sig20, Vgam,gam0, lam0,Vlam )
c= exp(x(2))+exp(x(3))-0.99;
ceq=[];
end
Even if the extra known variables aren't actually used in the computations of the constraints, they have to be there if you use additional arguments to fmincon to pass them in.
Incidentally, passing extra known parameters this way is antiquated. You should use anonymous or nested functions as described here. If you use these alternatives, you will not have to have to pass variables to functions that don't need them.
0 Comments
More Answers (0)
See Also
Categories
Find more on Optimization in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!