And yet another genetic algorithm

Root of: f(x) = e^x - tan(x)
Fitnessfunction: F(x) = f(x)^2
Goal: F(x) ~ 0
Effects used: mutation, no crossingover
Info: to avoid getting stuck in a local minimum choose populationsize well greater than children per generation

Parameters:

Populationsize

Children per generation
Mutation probability
Max mutation impact
Desired fitness
Generations

Results:

Create a new Population first!


(c) 2007 Phillip Kroll