NEOS Interfaces to BARON

Sample Submissions
WWW Form - XML-RPC

BARON

The NEOS Server offers BARON for the solution of mixed integer nonlinearly constrained optimization problems and global optimization problems. Problems for BARON can be submitted on NEOS in AMPL or GAMS format.

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 combining constraint propagation, interval analysis, and duality in its reduce arsenal with enhanced branch and bound concepts as it winds its way through the hills and valleys of complex optimization problems in search of global solutions.

BARON was developed and is currently maintained by Nick Sahinidis.

Availability of BARON on the NEOS Server is possible thanks to the generosity of The GAMS Development Corporation and the providers of software for the solution of the LP and NLP subproblems solved by BARON.


Using the NEOS Server for BARON/AMPL


The user must submit a model in AMPL format. Examples are provided in the examples section of the AMPL website.

The problem must be specified in a model file. A data file and commands files may also be provided. If the commands file is specified, it must contain the AMPL solve command; however, it must not contain the model or data commands. The model and data files are renamed internally by NEOS.

The commands file may include option settings for the solver. To specify solver options, add

  option baron_options 'OPTIONS';
where OPTIONS is a list of one or more of the available solver options for AMPL.

Web Submission Form
Model File
Enter the location of the AMPL model (local file)
Data File
Enter the location of the AMPL data file (local file)
Commands File
Enter the location of the AMPL commands file (local file)
Comments
Additional Settings


E-Mail address:
Please do not click the 'Submit to NEOS' button more than once.