Controlling Precision of Variable Bounds

I'm trying to solve a problem that has noninteger bounds for its variables,
the problem and the outputted solution attached. I'm invoking glpsol with
the command "glpsol --lp parents_allocated-pulp.lp -o
parents_allocated-pulp.sol --mipgap 0.000001".

The trouble is that the upper bound for my "x2" variable is being limited
to "217.351" instead of the given "217.3512" and I'm not sure why. Is there
some parameter I can pass to make it go past 3 decimal places for the upper
bound?

I tried --exact and every other parameter that I could see but none helped.
Is there some way to increase the number of digits in the bounds?

My output with 4.65:

GLPSOL: GLPK LP/MIP Solver, v4.65
Parameter(s) specified in the command line:
 --lp parents_allocated-pulp.lp -o parents_allocated-pulp2.sol --mipgap
0.000001
Reading problem data from 'parents_allocated-pulp.lp'...
2 rows, 7 columns, 8 non-zeros
6 integer variables, none of which are binary
22 lines were read
GLPK Integer Optimizer, v4.65
2 rows, 7 columns, 8 non-zeros
6 integer variables, none of which are binary
Preprocessing...
1 row, 2 columns, 2 non-zeros
2 integer variables, none of which are binary
Scaling...
 A: min|aij| =  1.000e+00  max|aij| =  7.000e+00  ratio =  7.000e+00
Problem data seem to be well scaled
Constructing initial basis...
Size of triangular part is 1
Solving LP relaxation...
GLPK Simplex Optimizer, v4.65
1 row, 2 columns, 2 non-zeros
*     0: obj =   1.100000000e+01 inf =   0.000e+00 (1)
*     1: obj =   3.300000000e+01 inf =   0.000e+00 (0)
OPTIMAL LP SOLUTION FOUND
Integer optimization begins...
Long-step dual simplex will be used
+     1: mip =     not found yet <=              +inf        (1; 0)
+     1: >>>>>   3.300000000e+01 <=   3.300000000e+01   0.0% (1; 0)
+     1: mip =   3.300000000e+01 <=     tree is empty   0.0% (0; 1)
INTEGER OPTIMAL SOLUTION FOUND
Time used:   0.0 secs
Memory used: 0.1 Mb (59394 bytes)
Writing MIP solution to 'parents_allocated-pulp.sol'...

Thanks for the help.

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