Does function linprog by interior point method have crossover process to obtain a basic solution?
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Greetings,
Currently, I am working on a linear programming problem. I used function linprog to solve it. However, I found if I specified either using interior point method or dual simplex method, I would get totally different solutions. The reason is the existence of multiple optimal solutions.
As we know, dual simplex method gives a vertex solution. How about interior point method? If interior point method has crossover process, I should get a vertex solution (basic solution). If it has not, I will get a inner point of the hyperplane of constraints.
Does function linprog by interior point method have crossover process to obtain a basic solution?
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Definitely not if your Matlab version is old enough, in which case the interior-point method offered is presumably the same as what is R2018a calls interior-point-legacy. I draw this conclusion from this test,
f=-[1,1];
A=-f;
b=5;
lb=[0,0];
ub=[1,1]*b;
opts=optimoptions('linprog','Algorithm','interior-point-legacy');
x_ipl=linprog(f,A,b,[],[],lb,ub,opts)
which yields the non-basic solution,
x_ipl =
2.5000
2.5000
With the interior-point algorithm of R2018a, I always seem to get a basic solution, but don't know why.
8 个评论
But even if the current or legacy interior-point algorithm does not have a "cross-over process", you should hardly ever see a non-basic solution. Linear programming problems with multiple solutions are numerically unstable. Small perturbations of the data will give you a basic solution, and you can never control which solution you are going to get. As an example,
opts=optimoptions('linprog','Algorithm','interior-point-legacy');
x_ipl_perturbed=linprog(f+randn(size(f))*1e-7,A,b,[],[],lb,ub,opts)
almost always gives the basic solution
x_ipl_perturbed =
5.0000
0.0000
or
x_ipl_perturbed =
0.0000
5.0000
Hi Matt
Thank for your help.
I did not use interior-point-legacy. What I used is just interior-point.
Is interior-point same as interior-point-legacy?
Is interior-point same as interior-point-legacy?
interior-point-legacy is the same as what old versions of Matlab called "interior-point".(That's what "legacy" means).
So, if you have selected "interior-point" in an old version of Matlab, you might see non-basic solutions.
Thank you Matt.
The version I am using is R2018a. Does "interior-point" method of R2018a have crossover?
Thank you
I do not know. I have yet to see a non-basic solution, however, in interior-point-R2018a.
But again, I'm not sure what you hope to achieve, even if you could confirm that interior-point has a cross-over process. Linear programming problems with multiple solutions are unstable. Even if the interior-point method did have a cross-over process, there can be no gaurantee that you would get the same basic solution that the dual simplex method (or any other solver) gives you.
Thank you very much! The reason why I ask, because I find interior-point of CPLEX by BIM is much slower than linprog of Matlab even I used same tolerance and constraints.
A = [1 1; 1 2];
b = [4 5]';
z = -[2 4];
%% Matlab interior
LPoptions = optimset('Algorithm','interior-point','MaxIter',2000,'TolFun',1e-6,'display','iter');
[MBarrier,fval,exitflag,output,lambda] = linprog(z, A, b, [], [], [0 0], [], LPoptions);
%% Matlab interior legacy
LPoptions = optimset('Algorithm','interior-point-legacy','MaxIter',2000,'TolFun',1e-6,'display','iter');
[MBarrier_legacy,fval,exitflag,output,lambda] = linprog(z, A, b, [], [], [0 0], [], LPoptions);
%% Matlab dual simplex
LPoptions = optimset('Algorithm','dual-simplex','Display','final','MaxIter',2000,'TolFun',1e-6);
[MDual,fval,exitflag,output,lambda] = linprog(z, A, b, [], [], [0 0], [], LPoptions);
You are right. I did this test, it is very clear that there is no crossover process in both interior-point and interior-point-legacy. I got a non-basic solution. The basic solution should be [0; 2.5].
I have a new question. Do you know from what version of matlab, new interior-point is used to replace old interior-point (interior-point-legacy)? Because I need to repeat the results simulated by old interior-point. And these two methods give different resultes when there are multiple optimal solutions.
Thank you very much!
When there are multiple optimal solutions to a linear program there is no way to ensure reproducibility of one solution on a different computer or software version. Such optimization problems are numerically unstable and so there is no way, through algorithm implementation, that you can hope to guarantee a particular output.
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