adding an elastic constraint

[Anthony Anderson]

Hello,

I'm interested in solving an IP problem, laid out as follows:

>>> prob = LpProblem("test", LpMinimize)
>>> x = LpVariable.dict("choice", range(1,10), lowbound=0, upbound=1, LpInteger)
>>> prob += sum(c[i]*x[i] for i in range(1,10)), "objective"

I would like to add an elastic constraint to prob, which is necessary for ensuring feasibility. Is it correct to "add" it as prob += elastic_contraint? 

Based on the documentation, I've tried the following:

>>> e = LpAffineExpression([(x[i],a[i]) for i in range(1,10)])
>>> c = LpConstraint(e, "constraint", sense=0, rhs=b)
>>> prob += c.makeElasticSubproblem(penalty=0, proportionFreeBound=0.05)

I just need some clarity on the last line, which produces the following error:

TypeError: Can only add LpConstraintVar, LpConstraint, LpAffineExpression or True objects

Thanks!

[Stuart Mitchell]

hi use prob.extend() instead

I'll have a look at changing the documentation

Stu

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Stuart Mitchell

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[Anthony Anderson]

I see what you mean. So something like the following:

>>> e = LpAffineExpression([(x[i],a[i]) for i in range(1,10)])

>>> c = LpConstraint(e, "constraint", sense=0, rhs=b)


>>> prob.extend(c.makeElasticSubproblem(penalty=0, proportionFreeBound=0.05))

Thanks for the help.

Anthony.

[Stuart Mitchell]

yup