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I'm currently looking for a mature GA library for python 3.x. But the only GA library can be found are pyevolve and pygene. They both support python 2.x only. I'd appreciate if anyone could help.
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To implement the two-point crossover, the following python code can be used. A multi_point_crossover function is defined where incoming arguments A & B represent the parents, X denotes an array of crossover points, and returning A & B represent the children.
C++: C++ is one of the best choices for genetic programming as they are highly computationally intensive. It provides a high-level of software environment to do complicated work in genetic programmings such as tree-based GP, integer-valued vector, and real-valued vector genetic algorithms, evolution strategy and more.
DEAP: Distributed Evolutionary Algorithms supports both Python 2 and 3: http://code.google.com/p/deap
Disclaimer : I am one of the developers of DEAP.
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Not exactly a GA library, but the book "Genetic Algorithms with Python" from Clinton Sheppard is quite useful as it helps you build your own GA library specified for your needs.
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