I have the following MIP problem. Upper bound for pre_6_0 should not be infinite because it is calculated from inp1, inp2, inp3, and inp4, all of which are bounded on both sides.
Maximize
obj: pre_6_0
Subject To
c1: inp0 >= -84
c2: inp0 <= 174
c3: inp1 >= -128
c4: inp1 <= 128
c5: inp2 >= -128
c6: inp2 <= 128
c7: inp3 >= -128
c8: inp3 <= 128
c9: inp4 >= -128
c10: inp4 <= 128
c11: pre_6_0 + 0.03125 inp1 - 0.0078125 inp2 - 0.00390625 inp3
+ 0.00390625 inp4 = -2.5
c12: - 0.0078125 inp0 + pre_6_1 = -2.5
c13: - 0.00390625 inp0 - 0.01171875 inp3 + pre_6_2 = 6.5
c14: - 0.0078125 inp0 + pre_6_3 = -1.5
c15: - 0.00390625 inp0 - 0.0078125 inp3 + pre_6_4 = 6.5
Bounds
pre_6_0 Free
inp0 Free
inp1 Free
inp2 Free
inp3 Free
inp4 Free
pre_6_1 Free
pre_6_2 Free
pre_6_3 Free
pre_6_4 Free
Generals
pre_6_0 inp0 inp1 inp2 inp3 inp4 pre_6_1 pre_6_2 pre_6_3 pre_6_4
The MIP best bound is infinite because no feasible integer solution exists.
Indeed, all the variables in your ILP have been restricted to general integer values (Generals section).
Here an example by using GLPK to solve the ILP.
15 rows, 10 columns, 25 non-zeros
10 integer variables, none of which are binary
...
Solving LP relaxation...
GLPK Simplex Optimizer, v4.65
5 rows, 10 columns, 15 non-zeros
0: obj = -8.000000000e+00 inf = 1.631e+01 (5)
5: obj = -3.750000000e-01 inf = 0.000e+00 (0)
* 8: obj = 3.000000000e+00 inf = 0.000e+00 (0)
OPTIMAL LP SOLUTION FOUND
Integer optimization begins...
Long-step dual simplex will be used
+ 8: mip = not found yet <= +inf (1; 0)
+ 8: mip = not found yet <= tree is empty (0; 3)
PROBLEM HAS NO INTEGER FEASIBLE SOLUTION
Time used: 0.0 secs
Memory used: 0.1 Mb (63069 bytes)