Classic problems solved with genetic algorithms

GA basic concepts:

• Gene / Individual = a possible solution of the problem. Usually, represented as a binary string or array.
• Population = a group of multiple individuals. Usually, only one population is used to solve the problem
• Crossover = the process of combining two individuals to generate another individual
• Mutation = the process of altering an individual (change 1->0 or 0->1 in the case of binary arrays)
• Selection = the process of selecting the individuals to form the next generation, based on their score (fitness function)

1. Initialize starting population/s
2. While not done: Crossover, Mutation, Selection, *

* = Migration, Reinsertion, etc