TMW suggest scaling the data so as to reduce the dynamic range. What I found to work was to rescale the objective function so that the nonzero coefficient with the smallest magnitude was 1.0. I also went through each inequality constraint, rescaling so that the smallest coefficient was 1.0 (I treated the right-hand-side constant as a coefficient as well).
intlinprog quits due to incorrect Relative Gap
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I am calling intlinprog indirectly using Problem-Based Approach (https://www.mathworks.com/help/optim/problem-based-approach.html). In PBA, the "solve" function calls intlinprog on behalf of the user.
I've run a few variations of my problem, and the outputs seem to make sense. I then ran into a variation whose output seems incomprehensible:
LP: Optimal objective value is -111.937682.
Optimal solution found.
Intlinprog stopped at the root node because
the objective value is within a gap tolerance
of the optimal value,
options.RelativeGapTolerance = 0.01 (the
selected value). The intcon variables are
integer within tolerance,
options.IntegerTolerance = 1e-05 (the default
value).
RETURN VALUES
fval = 111.0559
exitflag = OptimalSolution
output = struct with fields:
relativegap: 15.5046
absolutegap: 17.3740
numfeaspoints: 1
numnodes: 0
constrviolation: 2.2204e-16
message: 'Optimal solution found.
Intlinprog stopped at the
root node because the
objective value is within
a gap tolerance of the
optimal value,
options.RelativeGapTolerance
= 0.01 (the selected
value). The intcon
variables are integer
within tolerance,
options.IntegerTolerance
= 1e-05 (the default
value).'
solver: 'intlinprog'
The output indicates that intlinprog quits because the Relative Gap is within the 1% threshold. However, it is clearly above 15%.
What can I do to sleuth this down further? I am using MATLAB 2019a.
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