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Evolutionary algorithm implementation from CS/CSYS 352: Evolutionary Computation Fall 2022 instructed by Prof. Nick Cheney at University of Vermont

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Evolutionary Computation

Implementation of evolutionary algorithm for discrete binary genomes as seen in CS/CSYS 352: Evolutionary Computation Fall 2022 at University of Vermont instructed by Prof. Nick Cheney.

Features

  • Elitism
  • Random restart
  • 2-point list crossover
  • Truncation selection
  • Tournament selection
  • Scatter search (novelty search, diversity)
  • N-K Fitness Landscape (implemented by Prof. Nick Cheney)

Dependencies

  • Numpy
  • Matplotlib
  • Scikits.bootstrap
  • Scipy

Get Started

Type the following in the command line.

export PYTHONPATH=$PWD

Run the evolutionary algorithm on N-K landscape.

python run/run_assignment.py

Save PNG's of fitness and diversity graphs for the search.

python run/plot_assignment.py

Reference

  • Sean, Luke (George Mason University). 2010. Essentials of Metaheuristics: A Set of Undergraduate Lecture Notes. Optimization.

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Evolutionary algorithm implementation from CS/CSYS 352: Evolutionary Computation Fall 2022 instructed by Prof. Nick Cheney at University of Vermont

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