BARON is a computational system for solving nonconvex optimization problems to global optimality. Purely continuous, purely integer, and mixed-integer nonlinear problems can be solved with the software. The Branch-And-Reduce Optimization Navigator derives its name from its combining constraint propagation, interval analysis, and duality in its reduce arsenal with advanced branch-and-bound optimization concepts.
A systematic comparison on 1740 test problems shows that BARON has an edge over other global codes for NLP/MINLP. The test problems used in this comparison were originated from GlobalLib, CMU/IBMLib, MINLPLib, and PrincetonLib, respectively. This test set includes all problems from these libraries that are accepted by all solvers. These and additional test problems are available in a variety of formats. Below we give performance profiles for individual test sets.
|141 MINLPs from IBMLib||250 MINLPs from MINLPLib|
|369 NLPs from GlobalLib||980 NLPs from PrincetonLib|
- A general purpose solver for mixed-integer nonlinear optimization problems.
- Availability under the widely used AIMMS, AMPL, GAMS, JuMP, MATLAB, Pyomo, and YALMIP modeling environments.
- Developer-oriented modeling language that facilitates custom applications.
- Commercial versions of the code along with user support are available under a variety of platforms:
- The NEOS server for optimization provides free access to AMPL/BARON and GAMS/BARON, along with free computing time.
The best way to cite BARON is by citing:
- Tawarmalani, M. and N. V. Sahinidis, A polyhedral branch-and-cut approach to global optimization, Mathematical Programming, 103(2), 225-249, 2005. Click here for bibtex entry.
- Sahinidis, N. V., BARON 14.4.0: Global Optimization of Mixed-Integer Nonlinear Programs, User's manual, 2014. Click here for bibtex entry. Please make sure to cite the exact version of the code you are using. BARON 14.4.0 was the version available when this page was last updated.
We have listed out a few example files for a variety of problem types.