EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast.
With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems
... [More], from continuous to combinatorial ones.
Designing an algorithm with EO consists in choosing what components you want to use for your specific needs, just as building a structure with Lego blocks. [Less]
This is an interactive generative art application to evolve
images/textures/patterns/animations through an iterative process of random mutation and user-selection driven evolution. This process is also often referred to as "evolutionary art" or "genetic art". If you like lava lamps, and still
... [More] think the Mandelbrot set is cool, this could be the software for you. [Less]
The MOEA Framework is an open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose optimization algorithms and metaheuristics. A number of algorithms are provided out-of-the-box, including NSGA-II, ε-MOEA, GDE3 and MOEA/D.
... [More] In addition, third-party tools like JMetal and PISA directly integrate with the MOEA Framework.
The MOEA Framework targets an academic audience, providing the resources necessary to rapidly design, develop, execute and statistically test optimization algorithms. This includes over 40 test problems from the literature, and a suite of statistical tools for comparing and analyzing algorithm performance. [Less]
The Genetic Algorithm Utility Library (or, GAUL for short) is a flexible programming library designed to aid in the development of applications that use genetic, or evolutionary, algorithms. It provides data structures and functions for handling and manipulation of the data required for serial and
... [More] parallel evolutionary algorithms. Additional stochastic algorithms are provided for comparison to the genetic algorithms. [Less]
An object oriented library of an Genetic Algorithm, implemented in Java. Clear separation of the several concepts of the algorithm, e.g. Gene, Chromosome, Genotype, Phenotype, Population and Fitness Function. The fitness calculation is parallelized.
Algorithm::Evolutionary provides classes for performing simple evolutionary computation tasks, including definition of objects from XML and SOAP support. It should be interoperable with other EC libraries using SOAP.
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