PS. You also have not set an objective function, not sure, but it could be
why you have no termination

On Wed, May 21, 2025, 11:37 Dima Pasechnik <dimp...@gmail.com> wrote:

> It should be possible to construct the polyhedron determined by the
> feasible set of the LP, triangulate it, and do simplex by simplex or
> perhaps use various results relating volumes and presence of integral
> points in polyhedra.
>
> On Wed, May 21, 2025, 11:27 Vincent Delecroix <20100.delecr...@gmail.com>
> wrote:
>
>> Dear all,
>>
>> I have a 7 variables 3 constraints linear program that I want to solve
>> with integers
>>
>> x = M.new_variable(integer=True, nonnegative=True)
>> M.add_constraint(x[0] - x[1] + x[2] - x[3] - x[4] - 2 * x[6] == 2)
>> M.add_constraint(x[0] - x[1] + x[2] - 2 * x[4] - x[5] - x[6] == 2)
>> M.add_constraint(2 * x[0] - x[3] - x[4] - x[5] - x[6] == -1)
>>
>> However, with both
>>
>> M = MixedIntegerLinearProgram(solver="PPL")
>>
>> and
>>
>> M = MixedIntegerLinearProgram(solver="GLPK")
>>
>> The command M.solve() does not terminate in reasonable time... I do
>> not expect the system to have solutions, but I would like a proof of
>> it.
>>
>> One subtlety of the system is that there are (infinitely many)
>> positive integral solutions of the homogeneous version (ie linear
>> combination == 0). I wondered if that was the reason why it is harder
>> for a solver.
>>
>> If anyone knows of an alternative way to provide an open source
>> computer assisted proof that there is no solution I would be
>> interested.
>>
>> Best
>> Vincent
>>
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>>
>

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