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Bonmin is a solver for mixed-integer nonlinear programs. It is a global solver if the continuous relaxation is a convex program, and my hope is that it will perform better than the naive branch-and-bound I recently had to implement for a project (written in Python with cvxopt for quick development reasons, its performance was about the same as Yalmip bnb).

I struggled quite a bit yesterday to compile the library on my Mac running Snow Leopard though. Here is the final configuration I used, and so far that seems to be working (at least make test succeeded):

./configure FFLAGS="-arch x86_64" ADD_CXXFLAGS="-mmacosx-version-min=10.4" \
ADD_CFLAGS="-mmacosx-version-min=10.4" ADD_FFLAGS="-mmacosx-version-min=10.4" \
LDFLAGS="-flat_namespace" --with-blas='-framework vecLib' \
--with-lapack='-framework vecLib'

While I’m at it, if you want to compile Ipopt, the coin-or interior point optimizer on which Bonmin relies, then the following simpler configuration should do it:

./configure FFLAGS="-arch x86_64" --with-blas='-framework vecLib' \
--with-lapack='-framework vecLib'
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