A genetic algorithm

Approximation to: f(x) = e^x - tan(x)
Fitnessfunction: f(param1, param2, ...) = (e^param1-tan(param1))^2 + (e^param2-tan(param2))^2 +
Goal: f(param1, param2, ...) = 0
Effects used: mutation, crossingover

Parameters:

Populationsize
Children per generation
Mutation probability	%
Desired fitness
Number of parameters
Variation of params.
Generations

Results:

Create a new Population first!