BARON (short for Branch And Reduce Optimization Navigator) is a global optimization solver developed by The Optimization Firm. It is designed to find globally optimal solutions to a broad class of mathematical programming problems–including LP, NLP, MIP, and MINLP–and is the leading solver for MINLPs. Since 2001, BARON has been used by Fortune 500 companies, national research labs, and universities worldwide.

ALAMO communicates with external simulators using text files. To use a simulator, you must provide a wrapper script that:

1. Reads input.txt – contains the points ALAMO wants to simulate.
2. Calls your simulator – runs simulations at those points.
3. Writes output.txt – returns the results for ALAMO to read.

Example Setup

Example wrappers are included in the examples folder:

• Windows: C:\alamo\examples
• Linux: /usr/local/alamo/examples

One useful example is in the batpython folder:

• In e1.alm, the line simulator e1.bat tells ALAMO to use e1.bat as the simulator wrapper.
• e1.bat runs: 
  python2.7 C:\alamo\e1.py 
  (Replace python2.7 with the version installed on your system.)

In e1.py:

• Line 28 performs the simulation (e.g., x^2).
• Other lines handle I/O — reading from input.txt and writing to output.txt.

Customizing for Your Simulator

To integrate your own simulator, replace line 28 of e1.py with code that:

• Launches your simulator
• Reads input(s) from input.txt
• Writes results to output.txt

Examples for Python, MATLAB, and executable-based simulators are included in the ALAMO software package.

To request an ALAMO license:

1. Please visit the ALAMO Licenses page to view available types and pricing. Academic users, CAPD sponsors, and DOE researchers qualify for free licenses. 

2. Send an email to sales@minlp.com with the following information:

   1. Your name, email, and institution

   2. License type (e.g., annual single-user)

We will send payment instructions (if applicable), followed by your license file and activation details.

BARON uses a branch-and-reduce algorithm, which it pioneered in the 1990s, to solve MINLP problems to global optimality. This approach combines techniques like branch-and-bound, convex relaxations, and domain reduction to systematically eliminate regions of the search space that cannot contain the global optimum.

BARON's algorithmic innovations have set the standard in global optimization, and many other solvers have since followed its approach.

For a deeper explanation of the methods behind BARON, visit our BARON Publications page.