Problem when using linprog - interior-point algorithm
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Hello! I am trying to solve the following linear programming problem using MATLAB linprog function
optionsLin = optimoptions('linprog','Display','iter','Algorithm','interior-point',...
'OptimalityTolerance', 1e-8,'MaxIterations',1000,...
'ConstraintTolerance',5e-3);
c = 0.00*grad_displ + 0*1e-5*grad_compr;
LB = []; UB = [];
[Fopt,energy,exitflag] = linprog(c,AA,BB,KCon,bCon,LB,UB,optionsLin);
Since yesterday, the same code seems not to work when a relatively large number of constraints is imposed. Does anyone have any information about possible updates of the optimization toolbox that have caused this issue? Or anyone knows why I am experiencuing this difficulties? ANd above all, anyone that knows how to circumvent this problem?
I am using Matlab 2022b licence, but the same with matlab2023b and 2024a.
Thank you in advance!
9 comentarios
Torsten
el 21 de Mzo. de 2024
And what has changed since yesterday on your computer ? A new MATLAB installation ?
ANDREA MONTANINO
el 21 de Mzo. de 2024
Torsten
el 21 de Mzo. de 2024
What is the length of c = 0.00*grad_displ + 0*1e-5*grad_compr ?
Does it equal size(AA,2) and size(Kcon,2) ?
What error message do you get from "linprog" ?
It's almost impossible to find the problem with the information given.
ANDREA MONTANINO
el 21 de Mzo. de 2024
I always see the options as
optionsLin = optimoptions(@linprog,...
instead of
optionsLin = optimoptions('linprog',
in the MATLAB documentation. Does this change anything ?
What if you don't use the options command at all ?
Does the error appear right at the beginning of the computation or after a while when the solver could have finished ?
Matt J
el 21 de Mzo. de 2024
@ANDREA MONTANINO Run the code for us here in the online Matlab environment and see if you get a different result.
ANDREA MONTANINO
el 21 de Mzo. de 2024
Then you should test which of the optimoptions causes the problem by first using display, then display + algorithm etc.
Maybe it's the optimality tolerance because you work with c = 0 - thus you only try to find a feasible solution without optimizing at all.
ANDREA MONTANINO
el 21 de Mzo. de 2024
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