A simple genetic algorithm that uses crossover and mutation to solve the onemax problem.
In evolutionary computation, the onemax problem is where you evolve binary strings by maximizing the amount of 1's in each string.
For example, given a set of binary strings of length 5, the goal is to evolve strings that look like 11111, where each possible position contains a 1.
Run with Python 3 or greater.
python main.py
The following is a table demonstrating the minimum population size to find the global optimum for a given string size.
| String Size | Minimum Population Size |
|---|---|
| 20 | 8 |
| 50 | 12 - 14 |