contrebis/blue-jeans

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A framework for implementing genetic algorithms

dev-master 2013-12-08 02:28 UTC

This package is not auto-updated.

Last update: 2024-05-07 01:12:50 UTC


README

Introduction

This component is/will be a framework for solving optimisation problems using genetic algorithms.

The idea is you create a random pool of 'genomes'. Your genome class extends Genome and must interpret your bit string into a solution to your problem and calculate a fitness value for the solution. Good solutions are more likely to survive into the next generation.

Configurable options are:

  • Elitism: how many of the fittest genomes survive to the next generation intact.
  • Mutation rate
  • Crossover rate
  • Population size

An indicator of diversity can be calculated to show how much entropy remains in the system. If wanted, the mutation rate could vary to keep the diversity above a certain threshold.

TODO

  • Better test coverage (and remove whatever bugs are still lurking in there)
  • Some documentation
  • Optimise list collection class
  • Other performance optimisations
  • Add a license