Genetic algorithms work by creating a random population of solutions and try to find the correct solutions by imitating the process of natural selection. 
This version uses single point crossover selection and mutates 20% of the population. The parents fit is determined using the roulette wheel selection.
The user can define the size of the population and can see the number of the steps needed to reach a solution. 
The problem to be solved is to colour the connected/neighbor nodes of the given graph differently.