Hi, Michael,
Thanks for your input.
Are there some rules about the constraint selection in iterative LP?
Also, in my LP model, each constraint will introduce a new decision
variable.
decVarK_j >= decVarX_i * constValue_i - decVarT
If I used the solutions from solving the model with part of the constraints
and then replace the "decVarX_i" and "decVarT" with the solution values and
set
decVarK_j = decVarX_i * constValue_i - decVarT
then, check the constraint
decVarT + sum of (decVarK_j ) from j=1 to L <= [sum of
(constantValueP_i * decVarX_i) from i=1 to N ] * constantQ
If it satisfies the constraint, it means that the solution optimality still
can be kept ?
Any discussion/suggestions would be welcome.
thanks
On Thu, Sep 1, 2016 at 2:07 PM, Michael Hennebry <
[email protected]> wrote:
> On Wed, 31 Aug 2016, usa usa wrote:
>
> The problem is that the number of constraints of decVarK_i for i=1 to L
>> and L can be very large, e.g. 100,0000.
>>
>
> I think that the given constraints were not what you really intended.
>
> It means that it will have 100,000 constraints in the LP, which I want to
>> avoid.
>>
>>
>>
>> How to combine them so that I can reduce the size of the LP model
>> meanwhile
>> keeping all constraints satisfied ?
>>
>
> In general, you can't.
> The usual solution is iterative LP.
> Solve the problem with a subset of constraints.
> If the solution satisfies all your constaints, you are done.
> Otherwise select one or more violated constraints and resolve.
> Rinse and repeat until you have a solution or fatigue sets in.
> The tricky part is in the constraint selection.
> Unless you are doing something silly like working from an explicit list,
> it will be problem-specific.
>
> --
> Michael [email protected]
> "Sorry but your password must contain an uppercase letter, a number,
> a haiku, a gang sign, a heiroglyph, and the blood of a virgin."
> --
> someeecards
>
_______________________________________________
Help-glpk mailing list
[email protected]
https://lists.gnu.org/mailman/listinfo/help-glpk
