Welcome.

The Borg Multiobjective Evolutionary Algorithm (MOEA) is a state-of-the-art optimization algorithm developed by David Hadka and Patrick Reed at the Pennsylvania State University. Borg is freely available for academic and non-commercial use. Use this site to learn more about the Borg MOEA and request access to its source code.

Easy-to-use command line interface

Many-Objective

Borg efficiently captures the tradeoffs between many conflicting performance objectives, providing decision makers with detailed insight into their problem characteristics.

Adaptive Search

Borg uses an ensemble of search operators, auto-adapting their use at runtime to tailor itself to your optimization problem.

High-Performance

Written in efficient, high-performance ANSI C, the Borg MOEA wastes little time when solving your problem. Runs on Unix, Linux, Windows, and Mac.

Get It!

The Borg MOEA is freely available to academic and non-commercial users. Please complete the form below to request access to the source code. You will receive an e-mail within three business days with information about downloading the Borg MOEA. A high-performance computing version of the Borg MOEA is available for commercial use as part of the ExplorerDV product offered by DecisionVis, LLC.

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License Agreement *

THE PENNSYLVANIA STATE UNIVERSITY RESEARCH AND EDUCATIONAL USE LICENSE

BE ADVISED:  This Agreement is a legal agreement between "LICENSEE" (defined below) and The Pennsylvania State University, a non-profit corporation duly organized and existing under the laws of the Commonwealth of Pennsylvania ("UNIVERSITY").  By installing, downloading, accessing or otherwise using the SOFTWARE (defined below), LICENSEE agrees to be bound by the terms of this Agreement.  If LICENSEE does not agree with the terms of this Agreement, do not install, access, or use the SOFTWARE.

WHEREAS, Dr. Patrick Reed and Dr. David Hadka, employees of The Pennsylvania State University, have created and developed certain computer software entitled "BORG: Many-Objective Evolutionary Computing Framework" (the "SOFTWARE"); 

WHEREAS, patent protection for the SOFTWARE is being pursued by the UNIVERSITY including, but not limited to, United States patent 8,856,054;

WHEREAS, the UNIVERSITY is dedicated to fostering and advancing scientific research, this SOFTWARE is made available to the noncommercial research and educational community as a public service by the UNIVERSITY.  [Please contact the UNIVERSITY Office of Technology Management for information on other licensing arrangements (i.e. proprietary commercial applications)]. 

WHEREAS, the UNIVERSITY is the owner of and has the right to license the SOFTWARE and the associated patent rights; 

NOW THEREFORE, in consideration of the premises as well as the mutual promises and covenants set forth herein and for other good and valuable consideration, the receipt and sufficiency of which is hereby acknowledged, the parties hereby agree as follows:

 
1. Definitions

"LICENSEE" shall mean the person installing the SOFTWARE if it is solely for personal use by that person on the personal equipment of that person.  If the SOFTWARE is being installed on equipment for use by another legal entity, such as a corporation, limited liability company, partnership, or institution, then the person installing the SOFTWARE by proceeding with the installation certifies that he or she has authority to bind that legal entity to this Agreement; and that legal entity shall be considered to be the LICENSEE.


2. Grant and Obligations 

Under this License Agreement, LICENSEE is granted nonexclusive and royalty-free rights to practice any patent rights associated with the SOFTWARE, and the SOFTWARE may be used as-is or may be modified, provided that your practice or use is solely for noncommercial, research and education purposes.  You may not distribute the original version or modifications of the SOFTWARE for any purpose.  Both the original version and modified versions of the SOFTWARE may be copied and performed provided that the following terms and conditions are met: 

2.1	LICENSEE is affiliated with a nonprofit, noncommercial research and educational institution and shall identify the name of the institution and the names(s) of the users of the SOFTWARE to UNIVERSITY via Patrick Reed at the time that LICENSEE acquires this license.

2.2 	Modified versions of the SOFTWARE must clearly state that the work is a modification of the SOFTWARE and must prominently display the full SOFTWARE title and appropriate copyright notices.  Copyright management information (software identifier and version number, copyright notice and license) shall be retained in all versions of the SOFTWARE.

2.3 	If modified, the source code, documentation, and user run-time elements of the SOFTWARE should be clearly labeled by identifying the name of the person(s) and/or organization making the modifications, the date of modification, and a written description of the modifications. 

2.4	The UNIVERSITY may make modifications to the SOFTWARE that are substantially similar to modified versions of the SOFTWARE created by others, and may make, use, sell, copy, distribute, publicly display, and perform such modifications, including making such modifications available under this or other licenses, without obligation or restriction.

2.5 	Neither the name nor any of the logos of the UNIVERSITY may be used in advertising or publicity pertaining to the use or modification of the SOFTWARE without the specific, prior written permission of an authorized representative of the UNIVERSITY. 

2.6 	Any publications, reports, course lectures, and/or presentations that employ the SOFTWARE or its derivatives will acknowledge the use of the SOFTWARE or of any of its derivatives by citing the SOFTWARE developed by Dr. Reed and Dr. Hadka. 


3. Disclaimer of Warranty 

THIS SOFTWARE IS MADE AVAILABLE "AS-IS."  THE PENNSYLVANIA STATE UNIVERSITY DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, WITH REGARD TO THIS SOFTWARE, INCLUDING WITHOUT LIMITATION, THE WARRANTY OF NONINFRINGEMENT AND ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, AND IN NO EVENT SHALL THE PENNSYLVANIA STATE UNIVERSITY BE LIABLE FOR ANY DAMAGES WHATSOEVER, INCLUDING DIRECT, SPECIAL, INDIRECT, OR CONSEQUENTIAL DAMAGES RESULTING FROM ANY USE OR PERFORMANCE OF THE SOFTWARE INCLUDING, WITHOUT LIMITATION, LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION FOR CONTRACT, TORT (INCLUDING NEGLIGENCE) OR STRICT LIABILITY.

By checking this box, you understand and agree to the license terms above.

Publications.

Reed, P. M. and D. Hadka. Evolving Many-Objective Water Management to Exploit Exascale Computing. Water Resources Research, 50(10):8367-8373, 2014. View Details
Hadka, D. and P. Reed. Large-scale Parallelization of the Borg Multiobjective Evolutionary Algorithm to Enhance the Management of Complex Environmental Systems. Accepted to Environmental Modelling & Software, 2014. View Details
Giuliani, M. Agent-Based Water Resources Management in Complex Decision-Making Contexts. Doctoral Dissertation, Politecnico di Milano, 2013. Download PDF
d’Ervau, E. L. Optimizing Early-Warning Monitoring Systems for Improved Drinking Water Resource Protection. Master's Thesis, Universität Stuttgart, 8 October 2013. Download PDF
Woodruff, M. et al. Many-Objective Visual Analytics: Rethinking the Design of Complex Engineered Systems. Structural and Multidisciplinary Optimization, 48:201-219, 2013. View Details
Hadka, D., et al. Scalability Analysis of the Asynchronous Master-Slave Borg Multiobjective Evolutionary Algorithm The 16th International Workshop on Nature Inspired Distributed Computing (NIDISC) at the 27th IEEE/ACM International Parallel and Distributed Processing Symposium (IPDPS), Boston, MA, 20 May 2013. View Details
Woodruff, M. et al. Auto-Adaptive Search Capabilities of the New Borg MOEA: A Detailed Comparison on Product Family Design Problems. 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Indianapolis, Indiana, 17 September 2012. View Details
Hadka, D. et al. Diagnostic Assessment of the Borg MOEA on Many-Objective Product Family Design Problems. WCCI 2012 World Congress on Computational Intelligence, Congress on Evolutionary Computation, Brisbane, Australia, 10-15 June 2012, pp. 986-995. View Details
Reed, P., et al. Evolutionary Multiobjective Optimization in Water Resources: The Past, Present, and Future. (Editor Invited Submission to the 35th Anniversary Special Issue), Advances in Water Resources, 51:438-456, 2013. View Details
Hadka, D. and P. Reed. Diagnostic Assessment of Search Controls and Failure Modes in Many-Objective Evolutionary Optimization. Evolutionary Computation, 20(3):423-452, 2012. View Details
Hadka, D. and P. Reed. Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework. Evolutionary Computation, 21(2):231-259, 2013. View Details