Optimizing minimization with fmincon function
1 Ansicht (letzte 30 Tage)
Ältere Kommentare anzeigen
ektor
am 25 Mai 2019
Kommentiert: Sulaymon Eshkabilov
am 26 Mai 2019
Dear all,
I have this function which I minimize:
g=randn(1000,1);
u=randn(1000,1);
y=randn(1000,1);
options = optimoptions('fmincon','Display','off');
f = @(x) sum( ( y-x(1)*g-u*x(2) ).^2 );
nonlcon = @unitdisk;
x = fmincon(f,[0.2 0.02],[],[],[],[],[],[],nonlcon,options);
where
function [c,ceq] = unitdisk(x)
c = - x(2) +0.01;
ceq = [];
Is there a faster way of doing this minimization?
Thanks in advance.
0 Kommentare
Akzeptierte Antwort
Sulaymon Eshkabilov
am 25 Mai 2019
Hi,
By setting up the solver algorithm in the option settings, the simulation time cna be shortened substantially. E.g.
g=randn(1000,1);
u=randn(1000,1);
y=randn(1000,1);
options = optimoptions('fmincon','Display','off', 'Algorithm', 'active-set');
f = @(x) sum( ( y-x(1)*g-u*x(2) ).^2 );
nonlcon = @unitdisk;
x = fmincon(f,[0.2 0.02],[],[],[],[],[],[],nonlcon,options);
This algorithm shortens the computation time by about 50%. If you are not satisfied with this, you can investigate furthermore with the option settings for fmincon.
Good luck.
2 Kommentare
Sulaymon Eshkabilov
am 26 Mai 2019
hi,
Again if you post your example, that would be good to answer specifically w.r.t your problem constraints.
Weitere Antworten (0)
Siehe auch
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!