The Algorithm Design Manual
About the Book
Programming Challenges

The Stony Brook Algorithm Repository

Steven Skiena
Stony Brook University
Dept. of Computer Science

GA Playground

The GA Playground is a general purpose genetic algorithm toolkit where the user can define and run his own optimization problems. The toolkit is implemented in the Java language, and requires (when used as an application, in its full mode), a Java compiler and a very basic programming knowledge (just enough for coding a fitness function). Defining a problem consists of creating an Ascii definition file in a format similar to Windows Ini files, and modifying the fitness function in the GaaFunction source file. In addition, other methods can (optionally) be overwritten (e.g. the drawing method), other classes can be extended or replaced, and additional input can be supplied through Ascii files.

The GA Playground is primarily designed to be used as an application and not as an applet, since it requires re-compiling of at least one class and use of local file I/O. In addition, it is a little heavy as an applet, taking a relatively long loading time over the net. However, although its use as an applet does not enable defining new problems with new fitness functions, it enables extensive playing with many variations of an already existing problem type, by opening every aspect of the problem definition to the user. For example, any TSP test problem can be loaded through the 'Parameters' module. Used as an applet, the toolkit takes advantage of the Java cross-platform nature and the cross-world nature of the Internet, to bring a GA Playground to anyone interested in experimenting with genetic algorithms.

  • Download Files (local site)
  • Offical site

    Problem Links

    Constrained and Unconstrained Optimization (4)
    Traveling Salesman Problem (3)

    This page last modified on 2008-07-10 .