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A slightly modified version of the toy example in the README currently causes many linesearch-failures before the solver gives up. The underpinning problem seems to be that the inner loop breaks early and then the outer-loop concludes that the sub-problem was easy to solve, causing it to tighten \epsilon further.
Reproducer:
using MixedComplementarityProblems
M = [01; -10]
A = [10; 01]
b = [1; 1]
θ =rand(2)
G(x, y; θ) = M * x - θ - A'* y
H(x, y; θ) = A * x - b
mcp = MixedComplementarityProblems.PrimalDualMCP(
G,
H;
unconstrained_dimension =size(M, 1),
constrained_dimension =length(b),
parameter_dimension =size(M, 1),
)
sol = MixedComplementarityProblems.solve(MixedComplementarityProblems.InteriorPoint(), mcp, θ)
The text was updated successfully, but these errors were encountered:
A slightly modified version of the toy example in the README currently causes many linesearch-failures before the solver gives up. The underpinning problem seems to be that the inner loop breaks early and then the outer-loop concludes that the sub-problem was easy to solve, causing it to tighten
\epsilon
further.Reproducer:
The text was updated successfully, but these errors were encountered: