On Mon, 2016-04-11 at 14:48 -0400, Marco Montes de Oca wrote:
> Hi.
> I've found several cases where the solution's objective function
> values returned by the simplex method (versions 4.56 onward) and the
> interior point method (versions 4.56 onward) are different. However,
> the same problems o
On Tue, 2015-11-24 at 10:11 +0100, Yaser Tohidi wrote:
> Hi
>
>
> Thanks for your email. This is the result I get:
Your lp is badly scaled, so I suggest to use the following sequence:
glp_scale_prob(lps12, GLP_SF_AUTO);
glp_adv_basis(lps12, 0);
glp_simplex(lps12, NULL);
For more detai
On Mon, 2015-11-23 at 17:45 +0100, Yaser Tohidi wrote:
> Hi
>
>
> I have the attached GAMS file that I can solve in GAMS.
> But when I try to solve the .lp version (attached) by glpk (the c file
> is attached), I receive "LP has no primal feasible solution".
> Please let me know what I can do for
On Mon, 19 Aug 2013, Matteo Fischetti DEI wrote:
Just a last comment: in case of (primal) degeneracy, a vertex x* can be
optimal but a given associated basis B can still lead to negative reduced
costs, i.e., B can be "nonoptimal". Indeed, the test on reduced costs is only
a sufficient conditio
Just a last comment: in case of (primal) degeneracy, a vertex x* can be
optimal but a given associated basis B can still lead to negative
reduced costs, i.e., B can be "nonoptimal". Indeed, the test on reduced
costs is only a sufficient condition that can be violated by several
bases B associat
On Mon, 19 Aug 2013, sgerber wrote:
Thanks for all the helpful answers. One more clarifying question.
You mentioned:
It checks all extreme rays of a cone that includes the feasible region.
The number of rays is the dimension of the problem.
The cone you described is the intersection of the ha
Thanks for all the helpful answers. One more clarifying question.
You mentioned:
It checks all extreme rays of a cone that includes the feasible
region.
The number of rays is the dimension of the problem.
The cone you described is the intersection of the half spaces of the
active constraints.
On Sat, 17 Aug 2013, Andrew Makhorin wrote:
Is it possible to enumerate the neighboring feasible solutions of the
solution of an lp?
You may perform the post-optimal analysis by specifying the '--ranges'
option for glpsol, or with the routine glp_print_ranges. For more
details please see the
> Is it possible to enumerate the neighboring feasible solutions of the
> solution of an lp?
> I assume that in order to decide if the simplex algorithm can stop it
> is necessary to check all neighboring feasible solutions. Is this right?
> And if so is there a way of enumerating the neighborho
On Fri, 16 Aug 2013, sgerber wrote:
On 2013-08-16 11:48, Michael Hennebry wrote:
On Thu, 15 Aug 2013, sgerber wrote:
Is it possible to enumerate the neighboring feasible solutions of the
solution of an lp?
I assume that in order to decide if the simplex algorithm can stop it is
necessary to
As you observed, because of degeneracy some of the basic solutions
associated with different adjacent bases can in fact coincide.
Nevertheless, the number of different adjacent vertices can still be
very large (as Micheal said, their number can be "much larger than the
dimension of the problem
At 12:03pm -0400 Fri, 16 Aug 2013, Sam Gerber wrote:
On 2013-08-16 11:48, Michael Hennebry wrote:
On Thu, 15 Aug 2013, sgerber wrote:
Is it possible to enumerate the neighboring feasible solutions
of the solution of an lp?
I assume that in order to decide if the simplex algorithm can
stop it i
Hi Matteo
Thank you, this is very helpful. I am really interested in the
geometric neighborhood.
This sentence is paragraph is a little confusing:
In case of primal degeneracy, instead, you have a (possibly
exponential) n. of different bases B*_1, B*_2, associated with a
single vertex x
Hi Sam.
You have two related concepts here: one is vertex adjacency (a geometric
concept), and the other is adjacency between LP bases.
If you have no primal degeneracy (are you sure? this is *very*
unusual!), the two concepts coincide and you can enumerate all the
vertices x adjacent to a g
On 2013-08-16 11:48, Michael Hennebry wrote:
On Thu, 15 Aug 2013, sgerber wrote:
Is it possible to enumerate the neighboring feasible solutions of
the solution of an lp?
I assume that in order to decide if the simplex algorithm can stop
it is necessary to check all neighboring feasible solutio
On Thu, 15 Aug 2013, sgerber wrote:
Is it possible to enumerate the neighboring feasible solutions of the
solution of an lp?
I assume that in order to decide if the simplex algorithm can stop it is
necessary to check all neighboring feasible solutions. Is this right? And if
so is there a way o
Hi
Is it possible to enumerate the neighboring feasible solutions of the
solution of an lp?
I assume that in order to decide if the simplex algorithm can stop it
is necessary to check all neighboring feasible solutions. Is this right?
And if so is there a way of enumerating the neighborhood of
Firstly, you need to be specific about your meaning of
complexity. Mathmatically complexity is defined by
irreducibility. A problem is not more complex because it takes
glpk longer to solve it, or the special case interior method
described below.
Secondly we need to think about glpk solving things
Thanks for the answer Haroldo.
Does GLPK implement the "textbook" simplex method?
I am not an computational complexity analysis expert (not even an
algorithm one). As far as I know there is no simple way to calculate
the complexity of the simplex algorithm. As you wrote there exist some
worst
Hi Cenk,
On Sat, Oct 29, 2011 at 7:36 AM, Cenk Toker
wrote:
> Dear All,
>
> I have recently used GLPK to solve a sparse LP problem (a resource
> allocation problem for OFDMA) and found that the simplex solver is much
> faster than the interior-point solver.
> The problem has a special structure w
Dear All,
I have recently used GLPK to solve a sparse LP problem (a resource
allocation problem for OFDMA) and found that the simplex solver is much
faster than the interior-point solver.
The problem has a special structure where all vertices are integer.
Therefore, although the original under
Andrew Makhorin wrote:
>
>> I need to solve an Integer Linear Program but want to look at the result
>> of
>> an LP relaxation first.
>> What happens when the simplex or interior points algorithms are run on an
>> LP
>> problem that has variables of type GLP_IV?
>> Does it automatically perform
> I need to solve an Integer Linear Program but want to look at the result of
> an LP relaxation first.
> What happens when the simplex or interior points algorithms are run on an LP
> problem that has variables of type GLP_IV?
> Does it automatically perform LP relaxation and if so how is it perfo
I need to solve an Integer Linear Program but want to look at the result of
an LP relaxation first.
What happens when the simplex or interior points algorithms are run on an LP
problem that has variables of type GLP_IV?
Does it automatically perform LP relaxation and if so how is it performed?
T
> just a simple (and perhaps dummy!) question I cound #39;t find the
> answer on GLPK documentation: supose I have a glp_prob and solve it
> with glp_simplex. Now, if I add a new column does glpk solve the new
> problem from scratch?
If the LP presolver is disabled (it is disabled by default),
glp
Hi,
just a simple (and perhaps dummy!) question I cound't find the answer on
GLPK documentation:
supose I have a glp_prob and solve it with glp_simplex. Now, if I add a new
column does glpk solve the new problem from scratch?
I mean, it is possible to obtain 2 different solutions to a problem (but
> My name is Eduardo Valdivieso. I am a research student at Purdue
> University and I am new to Linear Programming and the solvers used
> to find their solutions. I was wondering what the difference between
> Solvers that use Interior point methods to solve their solutions and
> the Solvers that ar
On 11/07/06, Eduardo Valdivieso <[EMAIL PROTECTED]> wrote:
Hello,
My name is Eduardo Valdivieso. I am a research student at Purdue University and
I am
new to Linear Programming and the solvers used to find their solutions. I was
wondering
what the difference between Solvers that use Interior
Hello,
My name is Eduardo Valdivieso. I am a research student at Purdue University
and I am new to Linear Programming and the solvers used to find their
solutions. I was wondering what the difference between Solvers that use
Interior point methods to solve their solutions and the Solvers t
Hello,
what does it mean when the simplex loops (will not return) and how can I
avoid it ?
Dietrich Tent
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> using the simplex of the glpk I got an error message which says: the basis
> matrix is singuar. Can You tell me what is meant, because I think the basis
> matrix is the unity and therefore not singular.
This means that the matrix built from columns (of the original
constraint matrix) correspo
Hello ,
using the simplex of the glpk I got an error message which says: the basis
matrix is singuar. Can You tell me what is meant, because I think the basis
matrix is the unity and therefore not singular.
Yours sincerly
Dietrich Tent
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