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<div class="moz-cite-prefix">Sergey,<br>
<br>
A failing in standalone Clp - it should have warned you that the
scaled problem was optimal while the unscaled one was not feasible
- the solution from that does indicate column 0 is infeasible. If
you are calling clp then check primary status and also secondary
status - it would have been 2 -<br>
<br>
2 - scaled problem optimal - unscaled problem has primal
infeasibilities<br>
<br>
Clp saw that the elements of the matrix were very very small and
did some scaling to make the problem more stable. Unhappily the
scale factors for the first two columns were greater than 1.0e9!!
So it thought that -53.8/1.0e9 was a small negative value within
tolerance.<br>
<br>
The quick fix is to turn scaling off. However it is never a good
idea to have elements such as 1.2e-11 - maybe better to change
units to multiply all constraints by 1.0e3 or 1.0e6.<br>
<br>
John Forrest <br>
<br>
On 07/10/16 02:41, sergey pankov wrote:<br>
</div>
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cite="mid:CAAYPm4K2UDUkf0mPNpzbhj2wo7h-hfZ_Eyv0ucRmqZTe_nbdBQ@mail.gmail.com"
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<div>Hi,<br>
<br>
</div>
I am new to CLP (and to this mailing list). I have been
using CLP in my code for several days and encountered a LP
program that CLP thinks it solved successfully, but the
solution is out of bounds. I am using a ClpSimplex model
(as in minimum.cpp example). Here is the solution
(columns):<br>
<br>
Primal Dual Lower
Upper Cost<br>
0 c -53.8172 0.00000 0.00000
1.79769e+308 1.32630e-06<br>
1 c 49.9853 0.00000 0.00000
1.79769e+308 1.01542e-06<br>
2 c 0.0943604 0.00000 0.00000
1.79769e+308 0.00758213<br>
3 c 0.0731115 0.00000 0.00000
1.79769e+308 0.0170572<br>
4 c 1.61406 0.00000 0.00000
1.79769e+308 0.000855447<br>
5 c 7.37729e-07 0.00000 0.00000
1.79769e+308 50.0000<br>
<br>
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As you can see, the first value is negative, below the lower
bound. I saved the model to a .mps file, it is attached. Am
I doing something wrong? Is it me or CLP?<br>
<br>
</div>
Any help is highly appreciated, thank you very much in
advance.<br>
<br>
</div>
Sergey<br>
</div>
<br>
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