Welcome

Jenes (read as "genes" or "jeans") is an optimized library for genetic algorithms in Java. The library is designed to be fast and memory light, but still very easy to use. The library is an open source project promoted by Computational and Intelligent Systems Engineering Laboratory at University of Sannio  and hosted at sourceforge.com.

Jenes main site has been moved to a new location, please follow this link to keep in touch!

Features

  • Optimized architecture and memory usage
  • Modular and highly reconfigurable algorithms
  • Strong type checking
  • Available for Java 1.5+
  • Log of experiments in MS Excel and .csv files
The complete features list is described here.

Download

Jenes is free and open source software. You can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation.

THE LATEST RELEASE IS 1.3.0 [STABLE]
We are very interested in any feedback you might have, including noticed bugs, details of how you're using Jenes and what you think needs improvement.

You can email us at jenes@ciselab.org

The more feedback we get, the more we can improve Jenes.

If you have bugs to report please follow  this link at sourceforge.

If you have new features you would like to see in the upcoming releases, post them here at sourceforge.

If you are using jenes for your work, please just drop a line to our mailbox.

Thanks for your support!

Getting Started

Programming Jenes is really intuitive and only few minutes are required to get started with it. Before proceeding with the programming basics, it can be useful to understand how a genetic algorithm is structured in Jenes.
We prepared a collection of few tutorials in order to introduce the concepts behind the programming model of Jenes.
  1. Tutorial 1: A simple boolean problem
  2. Turorial 2: Structuring an advanced genetic algorithm
  3. Tutorial 3: Redefining genetic operations
  4. Tutorial 4: How to use SImpleGA
  5. Tutorial 5: ObjectChromosome
  6. Tutorial 6: Using local genetic algorithm goals
A complete description of the architecture is now avaible following the link.

A comparison with other libraries will be available soon.

Development Team

  • Luigi Troiano
  • Davide De Pasquale
  • Marco Merola
Former Contributions
Pierpaolo Lombardi, Giuseppe Pascale, Thierry Bodhuin


At Sourceforge

News

  • Release 1.3.0 Release 1.3.0 is public for download.WHAT'S NEWEnhancements:- New AlgorithmStage allows to wrap an algorithm as a stage in order to make it part of another ...
    Posted Aug 16, 2009, 2:51 AM by Luigi Troiano
  • Release 1.2.0 Release 1.2.0 [stable] is public available. It can be downloaded at sourceforge. Online documentation is avaliable here.
    Posted Feb 8, 2009, 11:58 PM by Luigi Troiano
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