I have the following integer linear programming problem which assigns values as expected, but when I add certain constraints, the objective function seems to become vacuous. I am not sure what to make of it. I am using python to solve the problem.
Non Vacuous formulation
score12 = 1
score21 = -1
C = 1000000
maximize : (w12 - s12) * score12 + (w21 - s21) * score21
subject to:
d12 = x2 - x1
d21 = x1 - x2
d12 - w12*C <= 0
d21 - w21*C <= 0
d12 + (1 - w12)*C > 0
d21 + (1 - w21)*C > 0
d12 + s12*C >= 0
d21 + s21*C >= 0
0 <= xi <= 1 , continuous
0 <= wij, sij <= 1, integer
The objective function is as expected:
MAXIMIZE
-1*s_12 + 1*s_21 + 1*w_12 + -1*w_21 + 0
And the solution is as expected:
('d_12', '= ', 0.0)
('d_21', '= ', 0.0)
('s_12', '= ', 0.0)
('s_21', '= ', 1.0)
('w_12', '= ', 1.0)
('w_21', '= ', 0.0)
('x_1', '= ', 0.0)
('x_2', '= ', 0.0)
But when I add the following constraints, or just either one:
d12 - (1 - s12)*C < 0
d21 - (1 - s21)*C < 0
Python changes the objective function to:
MAXIMIZE
0*__dummy + False
SUBJECT TO
... omited
I'm not what to make of it, the solution becomes vacuous:
('__dummy', '= ', None)
('d_12', '= ', 0.0)
('d_21', '= ', 0.0)
('s_12', '= ', 1.0)
('s_21', '= ', 1.0)
('w_12', '= ', 1.0)
('w_21', '= ', 1.0)
('x_1', '= ', 0.0)
('x_2', '= ', 0.0)
