Use as a regular LP solver -> no API to forcibly set the objective.

[SylvainCorlay]

The only way I could find to specify the objective function for the LP was to have all the constraint strengths be equal to zero except one, which is made so that the corresponding slack variable is what I want to minimize (up to a constant).

Is there a more elegant way to do this?

[sccolbert]

Rather than trying to reason about how the solver is building it's internal objective function, just create your own and minimize the result:

a = Variable('a')
b = Variable('b')
c = Variable('c')

cn1 = a <= 2
cn2 = b >= -3
cn3 = (c == 0) | 'weak'  # minimize objective
objective = 2 * a + 3 * b == c

solver.addConstraint(cn1)
solver.addConstraint(cn2)
solver.addConstraint(cn3)
solver.addConstraint(objective)

solver.updateVariables()

[sccolbert]

Please close this issue if that answers your question.

[SylvainCorlay]

Yes it does, thanks.