GAMS — The Solver Manuals - Available Software

48 COIN-OR
also found their way into the regular GAMS distribution. They are currently available for Linux (32 and 64 bit),
Windows (32 and 64 bit), Sun Solaris (Intel 64 bit), and Darwin (Intel 32 bit) systems. With the availability
of source code for the GAMSlinks the user is not limited to the out of the box solvers that come with a regular
GAMS distribution, but can extend and build these interfaces by themselves.
As of GAMS Distribution 22.8, available solvers include:
• CoinBonmin 0.99: Basic Open-source Nonlinear Mixed Integer programming
(model types: LP, RMIP, MIP, DNLP, NLP, RMINLP, MINLP, QCP, RMIQCP, MIQCP)
• CoinCbc 2.1: COIN-OR Branch and Cut
(model types: LP, MIP, RMIP)
• CoinGlpk 4.26: Gnu Linear Programming Kit
(model types: LP, MIP, RMIP)
• CoinIpopt 3.4: Interior Point Optimizer
(model types: LP, RMIP, DNLP, NLP, RMINLP, QCP, RMIQCP)
• CoinScip 1.00: Solving Constrained Integer Programs
(model types: LP, MIP, RMIP)
For more information see the COIN-OR/GAMSlinks web site at https://projects.coin-or.org/GAMSlinks.
2 CoinBonmin
GAMS/CoinBonmin brings the open source MINLP solver Bonmin from the COIN-OR foundation to the broad
audience of GAMS users.
Bonmin (Basic Open-source Nonlinear Mixed Integer programming) 0.9 is an open-source solver for mixedinteger
nonlinear programming (MINLPs), whereof some parts are still experimental. The code is developed in
a joined project of IBM and the Carnegie Mellon University. The COIN-OR project leader for Bonmin is Pierre
Bonami.
Bonmin implements five different algorithms:
• B-BB: a simple branch-and-bound algorithm based on solving a continuous nonlinear program at each node
of the search tree and branching on variables (default)
• B-OA: an outer-approximation based decomposition algorithm
• B-QG: an outer-approximation based branch-and-cut algorithm (by Queseda and Grossmann)
• B-Hyb: a hybrid outer-approximation/nonlinear programming based branch-and-cut algorithm
• B-Ecp: an ECP cuts based branch-and-cut algorithm a la FilMINT
The algorithms are exact when the problem is convex, otherwise they are heuristics.
For convex MINLPs, experiments on a reasonably large test set of problems have shown that B-Hyp is the
algorithm of choice (it solved most of the problems in 3 hours of computing time). Nevertheless, there are cases
where B-OA is much faster than B-Hyb and others where B-BB is interesting. B-QG corresponds mainly to a
specific parameter setting of B-Hyb where some features are disabled. B-Ecp has just been added to Bonmin and
is still experimental. For nonconvex MINLPs, it is strongly recommend to use B-BB, even though it is only a
heuristic for such problems too.
For more information we refer to
• the Bonmin web site https://projects.coin-or.org/Bonmin and