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Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. ...

This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.

GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.

EZvolve Foundation Classes is a set of data types and utility classes for use with evolutionary algorithms. Currently implemented support for bit string encoding, populations, fitnesses, fitness functions, probabilities, and probability vectors.

This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.

Simple genetic programming framework. Features a robust set of interfaces and standard implementations for rapid development and ease of experimentation.

The SBMLevolver is an evolutionary algorithm package that creates SBML models with user-specified properties and behaviour from a given set of building blocks. Applications lie in network reconstruction and synthetic biology.