RE: [Help-glpk] having problem with solver (numerical instability ?)

[Sayan Mitra]

Thanks for your response!

However, it is not clear to me how I can scale this problem. The large
number M arises from the "Big M" method for linearizing products of
binary and real variables. As I have mentioned before, if I reduce M,
then the solver complaints with :

lpx_simplex: numerical instability (primal simplex, phase II)

Best regards,
sayan



On Tue, 2 Mar 2004, Robert Horvath wrote:

>
>
> For me it seems like your problem is badly scaled (meaning the coefficient
> matrix A has elements very small in absolute value and very large as well).
> 1. Try to scale your problem first.
> 2. If 1. did not work, try to decrease the number M to as small a value as
> possible for your problem.
>
>
> Regards
> Robert
>
>
>
> -----Original Message-----
> From: address@hidden
> [mailto:address@hidden On Behalf Of
> Sayan Mitra
> Sent: Tuesday, March 02, 2004 1:55 AM
> To: address@hidden
> Subject: [Help-glpk] having problem with solver (numerical instability ?)
>
> Hello,
>
>     I am having the following difficulty with the solver; can anyone offer
>     fixes or a way to get around this?  In the following constraints, aa[i]
> is
>     an array of booleans, y[i] is real positive, e is a small number (set to
>     0), and M is a large number (set to 10.E+8),
>
>     s.t. effect_1{i in J}:         y[i] >= aa[i]  * e ;
>
>     s.t. effect_2{i in J}:         y[i] <= aa[i]  * M ;
>
>     therefore, when aa[i] is 0, then y[i] should be 0, but in the solution I
>     am getting positive values. I am given to believe that this is an issue
>     with the numerical instability of the solver, because if I reduce the
>     value of M, I get:
>
>     lpx_simplex: numerical instability (primal simplex, phase II)
>
>     Will look forward to your responses,
>
>     Thanks,
>
>     sayan
>
>
>
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