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]
DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelization mechanism such as multiprocessing and SCOOP. The following documentation presents the
... [More] key concepts and many features to build your own evolutions. [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]
Elf is a meta-language framework for genetic programming. Elf provides the infrastructure and basic commands necessary for defining a language, or instruction set, with which to evolve solutions to any algorithmic challenge. Solutions are themselves simple (or complex) programs built from these
... [More] simple assembly-esque languages. Elf also provides tools for generating and improving (via evolution by mutation and selection) a population of candidate solutions. [Less]
An efficient, stable research evolutionary computation and genetic programming research toolkit written in Java. Download at the ECJ Home Page, not here. This is an old repository. For the latest CVS repository, go to the ECJ repository at java.dev
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