Using genetic algorithms

A genetic algorithm (GA) is a method of evolutionary algorithm (EA). They are particularly useful when we want to write predictive algorithms in which only the strongest is selected and the rest are rejected. This is how it gets its name. So at every iteration it mutates, does a cross-over, and only the best is selected for the next iteration of population. The idea behind genetic algorithms is that after multiple iterations only the best possible candidates are left.

Getting ready

To work through this recipe, you will need a machine running Windows with an installed version of Visual Studio.

How to do it…

In this recipe, we will find out how easy it is to write a genetic algorithm:

void crossover(int &seed);
void elitist();
void evaluate();
int i4_uniform_ab(int a, int b, int &seed);
void initialize(string filename, int &seed);
void keep_the_best();
void mutate(int &seed);
double r8_uniform_ab(double a, double b, int &seed);
void report(int generation...