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