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genetica

Python library for minimization of a function using genetic algorithms in parallel.

Requirements:

  • mpi4py - MPI parallelization
  • matplotlib - graphical representation of results

Content:

  • fitness.py - defines function to minimize, as an example function f(x,y) = 0.1x^2 + |y| is minimized
  • Environment.py - sets the general structure of the algorithm
  • Population.py - defines properties of a populations
  • Individual.py - defines properties of an individual chromosome
  • IO.py - basic output
  • ioo.py - output with graphical representation
  • runGA.py - launches the algorithm

This work was supported by the National Science Foundation (NSF) CAREER award CHE–1255641 and the Bournique Memorial Fellowship by Marquette University.