Hi,

I get below solutions

  (gdb) p glp_get_col_val(lp, 'n', 7)
  $4 = 0
  (gdb) p glp_get_col_val(lp, 'c', 0)
  $5 = 1
  (gdb) p glp_get_col_val(lp, 'c', 1)
  $6 = 1
  (gdb) p glp_get_col_val(lp, 'c', 2)
  $7 = 1
  (gdb) p glp_get_col_val(lp, 'c', 4)
  $8 = 1.0000000000000002

for the following constraint.

  n7 - c0 - c1 - c2 - c4 >= -4

n7 should be greater than 0, but because of rounding errors it passes
the constraint check.

  (gdb) p (0 - 1 - 1 - 1 - 1.0000000000000002) >= -4
  1

What's the recommended way of solving such problems? I looked at ml
archives and found out that people use glp_scale_prob() method. But for
my particular case -- where I just check if (nx == 0.0) and if (cx ==
1.0) -- I couldn't figure out which option to use with glp_scale_prob()
method. Any ideas?


Regards.


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