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This repository contains the source codes used during the seminar on Evolutionary algorithms I.

There is a number of files:

  • sga.py is the basic implementation of the Simple Genetic Algorithm from scratch
  • partition.py is the implementation of an evolutionary algorithm for the set partition problem - partitioning a set of natural numbers into K = 10 subsets with the same sum
  • cont_optim.py is the implementation of a basic evolutionary algorithm for continuous optimization
  • co_functions.py is the implementation of a few continuous optimization benchmarks
  • utils.py contains implementation of simple utilities for logging the progress of the evolutionary algorithm and for making plots for comparison of multiple EAs
  • plotting.py contains a simple script intended to be edited in order to create plots of any experiments using the stored log files

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The source codes for the Evolutionary Algorithms I course - in Python.

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