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Test that getsolution is feasible when problem is Unbounded #144

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Test that getsolution is feasible when problem is Unbounded #144

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24 changes: 24 additions & 0 deletions test/linproginterface.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -192,6 +192,30 @@ function linprogsolvertest(solver::AbstractMathProgSolver, eps = Base.rtoldefaul
@test getconstrLB(m)[i] <= getconstrsolution(m)[i] + eps
@test getconstrsolution(m)[i] <= getconstrUB(m)[i] + eps
end

# Tests that getsolution is feasible when the problem is unbounded
# so that getsolution() + λ getunboundedray() is feasible for any λ >= 0
# See https://github.com/JuliaOpt/MathProgBase.jl/pull/144

# Max x
# s.t. x >= 1
# x unbounded
# y <= -1
loadproblem!(m, [1. 0.], [-Inf, -Inf], [Inf, -1], [1., 0.], [1], [Inf], :Max)
optimize!(m)
@test MathProgBase.status(m) == :Unbounded
x = MathProgBase.getsolution(m)
@test 1 <= x[1] + eps
@test x[2] <= -1 + eps

# See https://github.com/JuliaOpt/Gurobi.jl/issues/80
# Min y
# s.t. x >= 1
loadproblem!(m, [1. 0.], [-Inf, -Inf], [Inf, Inf], [0., 1.], [1.], [Inf], :Min)
optimize!(m)
@test MathProgBase.status(m) == :Unbounded
x = MathProgBase.getsolution(m)
@test 1 <= x[1] + eps
end


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