This program implements a simple evolution strategy as defined by Rechenberg and Schwefel : Floating-point Chromosome with increments, random selection, random reproduction, with lambda+mu replacement and generational termination.
The operators are the standard ones in ES: uniform xOver and mutation, which includes mutation of the chromosome value and the sigma
The only thing the user has to define is, obviously, the fitness function, which in EO becomes a fitness function class, the initial population, which in this case is created randomly, and the parameters for mutation and crossover.
If you want a more powerful way of defining the GA, and more control over it, use other algorithm (EOAlgo class, like EasyGA).
alphabetic index hierarchy of classes